Analytics Engineer Remote Jobs in Ohio (US)
This page tracks remote analytics engineer openings that are location-eligible for Ohio.
This page tracks remote analytics engineer openings that are location-eligible for Ohio.
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427 Jobs
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We are on a mission to unlock the world's best food creators and bring their dishes to the doorstep of the masses.
Role Description Analytics Engineers at CookUnity are data product owners who sit in a single team on a mission to minimize time spent by analysts and data scientists discovering, understanding, and preparing data before launching into their work. Each analytics engineer has ownership and autonomy over a set of entities/tables in a domain, collaborating on a single data design from first principles that the team owns together. As their products mature, they merchandise them as Tableau Connections, extracts into sheets, or any other endpoint needed to achieve their mission. Some analytics engineers have an interest in data infrastructure and integrations, others in bringing their data to life through interactive visualizations, but all have the skills to work with unruly raw data, design analytics-friendly data products (including entities and flat tables), and build them to a production standard that the whole company can rely on. Everyone in data at CookUnity comes with a high agency mindset, a passion for collaborating with others, a pattern of achievement, and a sincere interest in investing in their own development. Responsibilities - Own Core Data Products - Design, build, and maintain dbt models in Snowflake that reflect key business logic and serve as reliable sources of truth. Define clear ownership, usage expectations, and roadmaps for your data products. - Build Trustworthy, Scalable Models - Develop models that are easy to use, tested, documented, and serve a wide range of stakeholders. Measure success through usage metrics, reduced support needs, and SLA coverage. - Ensure Reliability and Observability - Monitor pipelines, track schema changes, and implement testing and alerting to ensure consistent data quality and uptime. - Drive Iteration Through Feedback - Collect and act on feedback from users. Use metrics, interviews, and usage logs to continuously improve your data products and documentation. - Advance AI Adoption in Analytics - Champion the use of agentic and AI-assisted tools in data workflows. Lead pilots, measure impact, and scale successful practices across the team. - Collaborate Cross-Functionally - Work with Engineering, Product, and Ops to align on metrics, instrumentation, experimentation, and data needs. - Mentor and Raise the Bar - Review code, guide design decisions, and share knowledge to elevate the craft of Analytics Engineering within the team. Qualifications - 4+ years of experience in Analytics Engineering, Data Engineering, or a similar role working with modern data stacks (dbt, Fivetran/Airbyte, Airflow, Snowflake/BigQuery, etc.) - Deep understanding of data modeling principles (e.g. dimensional modeling, ELT best practices, testing strategies, etc.) - Proficiency in SQL and version control (Git), with experience shipping production-quality data pipelines - Experience collaborating closely with cross-functional stakeholders (Product, Engineering, Operations, etc.) to translate business needs into data solutions - Comfort navigating ambiguity in fast-paced environments, with a strong sense of ownership and problem-solving mindset - Familiarity with BI tools (e.g. Tableau, Hex, Looker) and a passion for enabling self-serve data culture - Excellent communication skills, with the ability to explain technical concepts to non-technical audiences Benefits - 💸 Get paid in USD - 🗺 Work remotely: design the life that you want - ⛱ Enjoy 15 days of vacation each year from the start date - 🎄 16 fully paid Argentinean holidays - 🩺 Healthcare Benefit: Monthly stipend to use in your preferred healthcare provider - 🗓️ 5-year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical - 🐣 Paid Family leave - 🕯 Compassionate Leave: 3-5 days each time the need arises - 🧘🏽♀️ Customize the benefits that suit your needs! Access a range of perks tailored to you, including learning opportunities, wellness memberships, delivery apps, and more through our comprehensive benefit platform - 🧑🏫 Personalized English coach
• Own the entire lifecycle of data delivery- architecting pipelines from raw sources through dbt models and semantic layers into final Looker dashboards. • Embed directly with stakeholders to scope complex business questions, execute rigorous analyses, and independently translate ambiguous requirements into clear, decision-ready answers.
• We are hiring a Senior Finance Analytics Engineer on the Finance Data Team to support data modeling, reporting, and designing data products for an AI-native consumption model. • Design and build dbt models that serve as the source of truth for Finance & Accounting reporting, planning, and analysis. • Partner directly with stakeholders in Finance, Accounting, Revenue, and FP&A to define metrics, shape requirements, and translate business logic into well-structured models. • Write and optimize complex SQL against our Databricks environment with attention to accuracy. • Uphold and evolve patterns for model design, testing, versioning, and data contracts across the dbt project. • Design the semantic layer and metrics definitions (MetricFlow, Cube, or equivalent) that both humans and agents query against. • Drive the documentation flywheel across dbt, Databricks, Confluence, and the semantic layer so that models, columns, and metrics are legible to LLMs and analysts alike. • Use AI tooling (Claude Code, Cursor, and our internal capabilities) as a daily part of your own development workflow.
Dedicated to making space "safe, sustainable, and secure", Slingshot Aerospace offers a range of services in the aerospace industry, including space object trac
Title: Senior Python Engineer Location: Washington United States Job Description: Meet Slingshot At Slingshot Aerospace, we're on a mission to make space safer and more secure for everyone. Our work directly impacts global security, disaster response, climate monitoring, and the critical infrastructure that connects our world. We're a team of builders, thinkers, and problem-solvers who believe that the next generation of space operations will be powered by better data and smarter software. We move fast, we're not afraid to fail, and we believe the best ideas can come from anywhere-whether you're in engineering, sales, product, or operations. If you want to work on something that truly matters, with people who care deeply about the impact we're making and help shape the future of an industry that's just getting started, you're in the right place. What You'll Be Launching Hiring for two Senior Python Engineers to help architect and build secure, scalable, high-performance data processing and intelligent application platforms in the Washington DC-Baltimore area. Work is mostly done remotely but regular site visits in the DC area are required. Requires deep expertise in Python, FastAPI, distributed event-driven systems, MongoDB, and in-memory data technologies such as Redis. The engineer will play a key role in system architecture, development of production-grade services and pipelines, and implementation of best practices across data ingestion, transformation, streaming, AI integration, and secure software delivery. Experience with Retrieval-Augmented Generation (RAG) systems and Agentic AI workflows is highly desirable. This team is actively re-platforming a mission-critical production data pipeline from a legacy first-generation architecture into a modern, cloud-native, event-driven platform. These are newly created positions-not backfills-established specifically to expand the engineering team responsible for designing and building the next-generation system alongside an experienced group of senior engineers and architects. This is a highly hands-on engineering role within a small, senior-level team focused on re-architecting a high-throughput, mission-critical data platform. Engineers will work across several high-impact initiatives, including replacing tightly coupled synchronous processing patterns with asynchronous, event-driven microservices and defining the service boundaries, repository structure, and engineering standards that will support the platform long term. This is a true greenfield modernization effort. Candidates joining at this stage will have direct influence over architecture decisions, service ownership, development standards, and platform strategy. The environment combines modern cloud-native technologies with a serious compliance and security posture, including AWS GovCloud, FastAPI-based Python services, managed AWS infrastructure, Kubernetes with KEDA autoscaling, and Datadog observability. Engineers looking to work at the intersection of advanced distributed systems, cloud-native engineering, and government-grade security will find a strong fit in this opportunity. Your Mission (Should you choose to accept it) - Develop Python-based ETL frameworks, orchestration layers, and high-throughput data pipelines. - Implement and optimize real-time, event-driven streaming architectures using Kafka and/or RabbitMQ. - Build and scale FastAPI microservices with strong focus on performance, resilience, security, and observability. - Design MongoDB schemas, indexing strategies, and aggregation pipelines with attention to performance. - Implement caching layers, session management, and high-speed data access using Redis or similar in-memory stores. - Contribute to the design and implementation of RAG pipelines, vector search integrations, and retrieval optimization. - Implement Agentic AI workflows using LangChain and Crew AI. - Apply Secure SDLC practices across coding, code review, CI/CD, and deployment. - Participate in architecture reviews and contribute to engineering standards for distributed systems. - Troubleshoot complex data, system, and performance issues in production environments. - Support containerization, Kubernetes-native deployment patterns, and AWS cloud integrations. Pre-flight Checklist - Expert-level Python experience across ETL, microservices, and distributed data processing. - Strong FastAPI development and optimization experience. - Production experience with Kafka and/or RabbitMQ. - Strong MongoDB expertise: schema design, indexing, aggregation, sharding/replication. - Experience with in-memory databases such as Redis. - Hands-on experience implementing vector search or RAG-based retrieval pipelines. - Experience with agent-driven AI architectures and LLM-powered automation workflows. - Strong Linux proficiency and experience with Docker/Kubernetes. - Demonstrated ability to debug complex distributed or high-scale systems. - Hands-on AWS experience across compute, networking, and data services. - Proven application of Secure SDLC and secure engineering patterns. - Bachelor's or advanced degree in CS, Engineering, or related field. Strong preference for candidates with Active Top Security Clearance with SCI Eligibility Location: Washington DC Metro Area Salary: $150,000 - $220,000, equity and benefits US-based Candidates: we are currently only able to hire residents of the following U.S. states: AL, AZ, CA, CO, DC, FL, GA, HI, IL, IN, KS, MA, MD, MI, MN, MO, MT, NC, NJ, NM, NV, NY, OH, OK, OR, RI, TN, TX, UT, VA, WA, WI, WV We are unable to consider candidates residing in other U.S. states at this time. Internationally-based Candidates: we are currently only able to hire residents of the following locations: United Kingdom. We are unable to consider candidates residing in other countries at this time. Equity, Diversity & Inclusion are key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences, and backgrounds, who share a passion for creating a safer, more connected world. Diversity not only includes race and gender identity, but also national origin, citizenship, sex, color, veteran status, disability, genetic information, or any other protected characteristic that is part of one's identity. All of our employees' points of view are key to our success, and we embrace individuality.
Celigo is proud to be a 2025 Gartner Customers’ Choice for iPaaS and a Visionary in the Gartner Magic Quadrant for iPaaS for the second consecutive year. We are ranked #1 iPaaS on G2 for multiple quarters and named a Leader in both B2B/EDI and API Management. Remote-first culture, built on trust, collaboration, and transparency A high-growth, inclusive work environment where innovation thrives Lightspeed learning opportunities to keep you at the leading edge of your field Exceptional coworkers who challenge and inspire you daily
Role Description Celigo is looking for an Analytics Engineer to serve as the definitive owner of our business logic and the primary architect of our "Gold" data layer. You will bridge the gap between raw data and executive-level insights by transforming complex datasets into clean, validated, and highly performant tables. By applying software engineering rigors—such as version control, automated testing, and CI/CD—to our workflows, you will ensure our data warehouse remains a trusted "single source of truth." Your mission is to empower the company with the reliable data to drive decisions across Product, Finance, and GTM teams. - Develop and maintain scalable data models using dbt / Coalesce to transform raw data into clean, documented, and production-ready schemas. - Collaborate with Data Engineering and Data Analytics to ensure technical architecture supports business logic and reporting requirements. - Implement automated testing, data documentation, and observability frameworks to ensure a "single source of truth." - Optimize SQL queries and warehouse configurations to improve performance and manage compute costs. - Maintain version control workflows, CI/CD pipelines, and coding standards across the data team. - Support the semantic layer and BI data catalogs to enable self-service exploration. Qualifications - Strong belief in applying software engineering best practices (testing, versioning, peer review) to data workflows. - Ability to design modular data models (Star Schema, Kimball) that balance flexibility with system performance. - Proficiency in communicating technical trade-offs to both analysts and infrastructure engineers. - Degree in Computer Science, Mathematics, Statistics, or a related quantitative field. - 3+ years of experience in Analytics Engineering, Data Engineering, or a technical Data Analyst role. - Expert-level proficiency in SQL with a focus on writing efficient, maintainable, and readable code. - Hands-on experience with dbt / Coalesce and modern cloud data warehouses like Snowflake or BigQuery. - Familiarity with Git, pull request workflows, and command-line interfaces. Requirements - Experience with Python for data orchestration (e.g., Airflow) or advanced data manipulation. - Understanding of Fintech or SaaS-specific metrics such as ARR, churn, and financial reconciliation. Benefits - Remote-first culture, built on trust, collaboration, and transparency. - A high-growth, inclusive work environment where innovation thrives and ideas are implemented. - Lightspeed learning opportunities to keep you at the leading edge of your field. - Exceptional coworkers who challenge and inspire you daily. - Competitive compensation and benefits, including: - Three weeks of vacation (starting year one). - Wellness days and holidays to recharge. - Parental leave and a generous benefits package. - Monthly tech stipend. - Recognition and career development opportunities. Company Description Celigo is proud to be a 2025 Gartner Customers’ Choice for iPaaS. The only vendor to receive this award. Celigo is a Visionary in the Gartner Magic Quadrant for iPaaS for the second consecutive year. Celigo is ranked #1 iPaaS on G2 for multiple quarters and named a Leader in both B2B/EDI and API Management. Celigo is a leading intelligent automation platform that puts the power of automation in the hands of every team, unifying workflows from the predictable to the fully agentic in a single platform.
Angi is a tech company offering a digital marketplace to connect millions of homeowners across the United States with verified home improvement professionals and services. As an em
Role Description The Principal Analytics Engineer for Product Analytics will shape how product data is transformed and consumed, ensuring that both human analysts and AI agents receive consistent metrics, faster iteration, and trustworthy answers. This role is central to designing and evolving an analytics architecture that radically shortens the distance from complex business questions to validated insights. As a Principal leader, you will be the connective tissue across data engineering, analytics, and product teams—architecting pipelines, semantic layers, and quality practices so they work as a singular, cohesive system. The ideal candidate is a visionary technical simplifier with deep expertise in modern data stacks, a passion for developer/analyst velocity, and a proven ability to enable partner teams. You will play a dual role: - Empowering human analysts to spend less time debugging and more time driving strategy. - Hardening our data layer into a load-bearing, semantic infrastructure that AI tools can query accurately and safely. What you’ll do - Architecture & Semantic Layer Strategy - Data Product Ownership: Design, build, and evolve high-scale dbt models that transform raw upstream inputs into clean, well-documented, analytics-ready data products with clear contracts and ownership. - Agent-Safe Infrastructure: Implement critical guardrails, clear grain definitions, meaningful metadata descriptions, and approved access paths so AI tools and agents can query data accurately without bypassing governance. - Semantic Evolution: Shape how metrics are defined and exposed so that analysts, dashboards, and AI tools all return the same answer to the same question, turning the semantic layer into production-grade infrastructure for AI-powered BI. - Operational Excellence & Velocity - Friction Elimination: Translate recurring analyst pain points—such as ambiguous metrics, broken joins, or undocumented fields—into durable, reusable models, patterns, and shared interfaces. - Quality & Governance Standards: Set and hold the bar for what "done" means for a data product, embedding robust testing, freshness expectations, data catalogs, and metadata ownership into the development lifecycle. - Cross-Functional Alignment: Coordinate across data platforms and product teams to map use cases, eliminate duplicate work, surface technical tradeoffs early, and drastically reduce cycle times from business question to trusted answer. - Leadership & Enablement - Shared Frameworks: Collaborate with data and analytics engineering peers to establish and maintain global patterns, package management, and repository best practices. - Mentorship & Review: Raise the collective engineering bar across the organization by running technical reviews, hosting office hours, and leading pair-programming sessions with domain analysts and engineers. Qualifications - 12+ years of experience in analytics engineering, data engineering with heavy analytics partnership, or an equivalent technical data role. - Expert-level SQL and strong Python proficiency for advanced data work, with a proven track record of delivering on a modern data stack (transformation-as-code, orchestration, warehouses, and BI). - Experience with data governance tooling, including data catalogs, lineage systems, and policy-aware access patterns. - Exceptional cross-functional leadership skills with a history of influencing engineering and product teams without direct authority. - Strong technical communication skills, with the unique ability to explain complex modeling decisions to a product analyst without jargon, and to a platform engineer without oversimplifying. Preferred Qualifications - Hands-on experience working directly with dbt and Snowflake in a high-scale environment. - Practical experience implementing data mesh architectures or federated data ownership models. - Exposure to AI/LLM tooling as a data consumer, with a strong conceptual grasp of what clean, well-structured data requires to be successfully queried by AI agents and assistants. Benefits - The salary band for this position ranges from $165,000 - $240,000 commensurate with experience and performance. Compensation may vary based on factors such as cost of living. - This position will be eligible for a competitive year-end performance bonus & equity package. - Full medical, dental, vision package to fit your needs. - Flexible vacation policy; work hard and take time when you need it. - Pet discount plans & retirement plan with company match (401K). - The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world. We value diversity We know that the best ideas come from teams where diverse points of view uncover new solutions to hard problems. We welcome and value individuals who bring diverse life experiences, educational backgrounds, cultures, and work experiences.
Role Description Bamboo Health is seeking a Senior Analytics Engineer who is passionate about data and enthusiastic about creating user-facing data products. As Senior Analytics Engineer, you will work alongside the Analytics and Visualization team and internal stakeholders to develop reporting solutions powered by our unique data pipeline. Successful candidates will excel in creative problem-solving, cross-team collaboration, and independent thinking to leverage data in addressing customer challenges. If you are a self-starter eager to enhance healthcare delivery and thrive in a collaborative environment, this is the role for you! What You’ll Do - Design and manage data pipelines essential for supporting reporting solutions. - Develop innovative dashboards and reporting features to improve customer and user satisfaction. - Establish yourself as the technical authority on the reporting components of our product suite. - Foster collaboration among Agile teams and across functions to promote solution implementation. - Use data and advanced analytical methods to provide actionable insights to stakeholders. - Support a variety of business-aligned projects to meet organizational objectives. - Identify repetitive tasks and partner with team leads to implement scalable automation solutions. - Stay curious about emerging AI tools and how they can streamline or enhance work within your function. What Success Looks Like… - In 3 months… - Become familiar with our reporting offerings and key customer use cases. - Gain a strong understanding of our data pipeline and architecture. - Start building strong, collaborative relationships with peers on the Analytics team. - Identify at least one opportunity in your role to pilot or apply AI or automation. - In 6 months… - Expand your scope of influence to include other cross-functional stakeholders. - Develop new reporting pipelines and capabilities that align with user needs. - In 12 months… - Establish yourself as the technical expert on reporting components of our product suite. - Collaborate with various business areas to deliver analytics that improve decision-making. - Offer insights and direction on enhancing reporting and increasing efficiencies. Qualifications - A Bachelor’s Degree in a quantitative or technical discipline, such as mathematics, economics, computer science, statistics, or a similar quantitative field, is required. An advanced degree is a plus. - 5+ years of professional experience in data analytics. - Experience in designing user-friendly analytics solutions with Tableau, Looker, or similar data visualization software. - Ability to write SQL for collecting, cleaning, and aggregating data. - Solid understanding of database technologies (PostgreSQL, MySQL, DynamoDB) and ability to code for data collection. - Understanding data warehousing concepts and experience with platforms such as Amazon Redshift. - Solid working knowledge of Tableau, with experience in creating user-facing analytics solutions. - Solid understanding of Python, GitHub, and other standard development tools. - Comfort using or learning AI-supported tools (e.g., ChatGPT, CoPilot, or role-specific tools) to improve daily workflows. - A forward-thinking, curious mindset with an openness to experimenting with new technologies. - Strong analytical and problem-solving skills, with sound judgment and creativity in designing solutions. - Proven ability to thrive in fast-paced, high-growth, and rapidly evolving environments. - Ability to work effectively in a remote-first environment, ensuring high-quality virtual interactions with minimal distractions. - The ability to travel periodically for work. Benefits - Join one of the most innovative healthcare technology companies in the country. - Enjoy the freedom to create something with a highly supportive team. - Learn from working at the highest levels and on the company's most strategic priorities, including from world-class investors and advisors. - Receive competitive compensation that includes health, dental, vision, and other benefits.
Reddit is an online platform utilized by thousands of communities to connect and converse about a wide variety of topics, including TV and movie fan theories, s
• Be an Analytics Engineering leader within the Consumer organization and a key contributor and collaborator to the success of Data Science data quality, performance, reliability, and automation initiatives. • Be the data steward for Consumer products: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for product feature tracking, user retention analysis, A/B testing, and a large number of other data-driven activities. • Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines. • Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability. • Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service. • Provide technical guidance, mentorship, coaching and/or training to data scientists and other technical partners. • Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.
Affirm is a financial services company that is on a mission to provide its customers with “honest financial products that improve lives.” As an employer, Affirm maintains a rem
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. The Risk & Analytics team makes crucial decisions that direct Affirm’s business strategy. Our team designs and runs experiments to decide which product features to launch and which marketing campaigns to fund. We analyze performance not just to report on it, but to determine where to invest resources for maximum impact through building tools and analytical frameworks. We take ownership of the entire analytical lifecycle, from initial question to final business decision, ensuring Affirm grows efficiently and intelligently. The Credit team works cross-functionally with Machine Learning, Product, Engineering, Capital Markets, and Commercial teams to responsibly manage the risk profile of the business. We’re looking for a thoughtful, driven individual who wants to learn, grow, and solve hard problems. The team’s mandate is to enable sustainable growth while closely managing the profitability and resilience of our portfolio. As Affirm continues on an exciting growth trajectory; thinking through credit policies for new initiatives and products, shaping ongoing testing and experimentation, and being ready for navigating through any exogenous changes will be important problems to tackle. The ideal candidate brings exceptional analytical rigor, deep credit domain expertise, and the ability to influence stakeholders across both technical and non-technical teams. You thrive in ambiguity, can translate complex regulatory and economic insights into actionable credit strategies, and are comfortable operating at both strategic and execution levels. Come join us in our mission to change consumer finance through better data and technology, lower costs, and increased transparency while providing the best customer experience! What You’ll Do - Leverage advanced data analytics to derive insights and optimize credit strategies across products and geographies. - Partner with Engineering to design and build scalable risk models and credit risk capabilities. - Monitor portfolio performance and macroeconomic trends that impact loan outcomes; proactively adjust underwriting and marketing strategies to mitigate risk. - Collaborate closely with Product, Legal, and Compliance teams to interpret evolving regulatory and market requirements across jurisdictions, and translate them into credit policy, underwriting, and product design recommendations. - Engage and coordinate with external stakeholders — including merchants, vendors, and regulatory bodies — to align credit risk practices, ensure compliance, and strengthen strategic partnerships. - Oversee the development and execution of credit underwriting frameworks that balance growth, compliance, and risk mitigation goals. - Drive cross-functional discussions to ensure new product launches and market entries are aligned with risk appetite, operational capabilities, and local regulations. What we look for - Degree in Data Science, Computer Science, Engineering, Economics, or a related field, and 4+ years of experience (or equivalent senior-level experience) - Experience setting credit strategy for de novo products using Sandbox data, retrospective studies or archives - Experience in high-line unsecured lending, especially in the home improvement vertical - SQL, Python, or other scripting languages - Data mining, data visualisation, and statistical modeling - Applying machine learning techniques to credit risk management - Leveraging advanced analytics to develop and optimise credit strategies - Monitoring and interpreting model performance metrics across portfolios - Proven experience leading cross-functional initiatives that bridge Product, Legal, Compliance, and Engineering to align credit strategies with regulatory frameworks and business objectives. - Deep understanding of consumer lending regulations, fair lending principles, and regional market dynamics influencing credit policy and underwriting. - Ability to translate complex regulatory and economic insights into actionable credit and product strategies. - Demonstrated success mentoring high-performing analytical teams and driving data-informed decision-making at scale. - Exceptional communication skills with the ability to influence senior stakeholders across technical and non-technical functions. Pay Grade - M Equity Grade - 8 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA base pay range (CA, WA, NY, NJ, CT) per year: $180,000 - $230,000 USA base pay range (all other U.S. states) per year: $160,000 - $180,000 #LI-Remote Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities. We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include: - Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents - Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses - Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge - ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process. [For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
AI Risk Decisioning™ platform that helps organizations manage onboarding, fraud, credit, and compliance risks
• Understand stakeholder data needs across Ops, Finance, and the GTM org, including Sales, Marketing, BDR, and Customer Success, and translate those needs into clear technical requirements. • Define, build, and manage key data pipelines in dbt that transform raw data into canonical datasets. • Use AI tools, LLMs, and agents to accelerate analytics workflows, including data exploration, pipeline development, QA, documentation, dashboard creation, and stakeholder enablement. • Read, write, debug, and validate SQL, Python, dbt models, and AI-generated code to ensure outputs are accurate, reliable, and production-ready. • Establish high data integrity standards, SLAs, and QA processes to ensure timely and accurate data delivery. • Develop reliable dashboards to track core business, GTM, and operational metrics. • Build foundational data products, dashboards, automations, and internal tools that enable self-serve analytics across the company. • Bring a strong point of view on build vs. buy decisions across the GTM data stack, identifying where Oscilar should use off-the-shelf tools versus where we should build internally for speed, leverage, or differentiation. • Partner with GTM and Finance leaders to influence roadmap decisions from a data systems and analytics perspective. • Become an expert in Oscilar’s data models, business metrics, GTM systems, and broader data architecture. • Help shape a modern, AI-native analytics engineering function as Oscilar scales.
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SQL, Python, Airflow, dbt, Snowflake, Observability/Monitoring