Analytics Engineer Remote Jobs in Michigan (US)
This page tracks remote analytics engineer openings that are location-eligible for Michigan.
This page tracks remote analytics engineer openings that are location-eligible for Michigan.
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443 Jobs
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Join us on our journey toward a world with zero crashes, zero emissions, and zero congestion.
Description Work arrangement : Remote: This role is based remotely but if you live within a 50-mile radius of [Atlanta, Austin, Detroit, Warren, Milford or Mountain View], you are expected to report to that location three times per week, at minimum. The Safety Assurance for Effective Autonomous Driving Software (SAFE-ADS) department is part of GM's Global Product Safety, System, and Certification organization. Our mission is to help GM deliver trustworthy automated-driving products. As the central authority for automated driving system safety, SAFE-ADS brings together experts from across the company to develop and maintain a comprehensive safety case, including safety performance indicators for GM's automated-driving technologies. GM's vision is zero crashes, zero emissions, and zero congestion, and autonomous vehicle safety is essential to achieving that vision. The Team The AV Safety Engineering Analytics team supports safety-related decision-making across GM by developing analytics, metrics, and evidence from vehicle, simulation, and external data sources. The team supports both proactive safety monitoring and targeted investigations, and works across stakeholder groups to support engineering, validation, verification, and program decisions by turning complex technical data into usable guidance. The Role The AV Safety Engineering Analytics Engineer is an engineering role with a strong safety data science applied to physical systems focus, centered on developing the analyses, metrics, and evidence used to evaluate automated driving system safety and support decision-making. In this role, you will combine engineering judgment, data analysis, and statistical thinking to transform raw vehicle, simulation, and external data into safety metrics, investigations, and stakeholder-facing insights. You will work with cross-functional partners to define and productionize safety-relevant metrics, establish evidence and sufficiency criteria used to assess system performance and launch readiness, and communicate findings clearly to stakeholders. This role regularly supports systems, safety, testing, and verification activities by helping translate data into decision-useful metrics and evidence. Interactive visualizations and scalable data pipelines are important enablers in this role, helping analyses scale, increasing transparency, and turning complex results into usable stories for decision-making. What You'll Do - Define, prototype, and productionize safety and performance metrics for automated driving systems. - Establish analytic approaches and sufficiency criteria that support safety assessment, development decisions, and launch readiness. - Support proactive safety monitoring and targeted investigations tied to specific system-performance or safety questions. - Support systems, safety, testing, and verification stakeholders by comparing real-world and simulation-based results, identifying gaps, and helping improve the representativeness of evaluation methods. - Apply engineering and physics-based methods to process raw signals and derive meaningful representations of vehicle motion, driving context, and system behavior. - Distinguish sensor or pipeline errors from meaningful real-world outliers using engineering judgment and data validation methods. - Create interactive visualizations and reporting artifacts that communicate safety insights clearly, enhance transparency, and reduce barriers to interrogating source data in support of technical decision-making. - Build and maintain analytics infrastructure that supports safety assurance across development, validation, and deployment. - Develop reliable pipelines that ingest, transform, analyze, and publish data from vehicle systems, internal databases, simulation outputs, and external sources. - Optimize analytics code and workflows for scalable, automated cloud execution. Your Skills & Abilities (Required Qualifications) - Bachelor's degree in Computer Science, Mechanical Engineering, Vehicle Engineering, Physics, or a related field, or equivalent practical experience - 5+ years of experience analyzing large-scale driving, vehicle, robotics, or similar engineering data - 5+ years of experience in ADAS, autonomous vehicles, robotics, or a related technical domain - Experience with statistics relevant to large-scale engineering data analysis, including sampling, bias management, and experimental design - Experience transforming noisy time-series or sensor data into analysis-ready features or metrics - Strong problem-solving skills and a proactive, learning-oriented mindset - Strong communication and collaboration skills, with the ability to work effectively across technical teams - Strong programming skills in Python and SQL - Experience building and operating cloud-based analytics or data-processing workflows at scale - Experience in some combination of the following is expected: - Programming & Frameworks : Python, SQL - Cloud & Big Data : cloud-based large-scale processing including notifications, queuing, serverless functions, event-driven processing, infrastructure as code, containerization, process monitoring, process optimization, identity and access management, and service-to-service access - Statistics : descriptive statistics, managing bias in large data mining activities, experimental design, and sampling strategies - DevOps / Infrastructure as Code : CI/CD, versioning, Docker, Kubernetes, GitHub, Jira, Jenkins, Poetry, Terraform - Data Analysis & Visualization: Tableau, PowerBI, Plotly/Dash, Shiny, Pandas, NumPy What Will Give You a Competitive Edge (Preferred Qualifications) - Experience analyzing large-scale vehicle motion, driving context, automated-driving performance, or simulation data - Experience with driver behavior modeling, human performance benchmarking, causal inference, or counterfactual modeling techniques - Experience with systems engineering, verification and validation, simulation-based evaluation, scenario analysis, or work that bridges simulation and on-road safety assessment - Experience building stakeholder-facing dashboards or interactive analytics products - Experience with cloud or distributed data platforms, or with DevOps, CI/CD, containerization, or infrastructure-as-code workflows - Publications, conference participation, or other demonstrated engagement in vehicle-safety, safety-analytics, or related technical work GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE. This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate. #LI-SA2 About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Total Rewards | Benefits Overview From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us [email protected] or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
Landing is reinventing renting with flexible-lease apartments for people who want to say hello to possibility.
• Own Landing's dbt models, data pipelines, and warehouse architecture. • Maintain dbt model library — keeping models clean, tested, documented, and aligned with business data usage. • Manage Landing's ELT stack — including Stitch, Snowflake, dbt, and associated monitoring and orchestration tooling. • Establish a finance and operations data spine — authoritative source of truth for core executive KPIs, metric definitions, and warehouse logic. • Develop analytics engineering standards, tooling decisions, and long-term roadmap for data platform. • Foster cross-functional data partnerships with Engineering, FP&A, and Accounting — translate between technical infrastructure and business need. • Enforce data quality standards, testing frameworks, and metric governance practices. • Support executive, board, and investor reporting — work directly impacts high-stakes decision-making and fundraising.
• Design and develop data serving and semantic layers to support business needs ranging from traditional reporting to reverse ETL and LLM/AI implementations. • Develop data models for use by analysts and applications from across the business using modern dimensional modeling practices to efficiently serve accurate, consistent data. • Build and maintain robust, scalable data pipelines to extract, transform, and load (ETL, ELT) data from various sources into the data platform using both batch processing and event-driven patterns. • Create efficient, performant data models to support business requirements and analytics needs. • Implement and automate data quality checks and monitoring to ensure data accuracy and drive observability. • Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions and on-premises systems. • Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis. • Work closely with data analysts, data scientists, and business stakeholders to understand their data needs and deliver solutions. • Identify and resolve data-related issues and challenges for technical and non-technical stakeholders. • Support company-wide projects ranging from server migrations to mergers and acquisitions as a data and systems expert. • Automate data processes to improve efficiency and reduce manual effort. • Implement modern concepts like metadata-driven pipelines and Infrastructure-as-Code that will play a key role in a scalable, resilient data platform. • Document data processes, architecture, and workflows.
Workato is a computer software company that has developed an enterprise automation platform with easy-to-use automation and integrations. The company fosters a
Role Description - Design, build, and maintain scalable data pipelines to process and analyze large datasets - Integrate data from various sources, ensuring data quality and consistency - Develop and manage ETL processes to transform raw data into usable formats - Create and maintain data models to support reporting and analytics - Work closely with operations analysts and stakeholders to understand data requirements and deliver solutions - Optimize data processing workflows for performance and scalability - Implement data validation and quality assurance processes to ensure accuracy and reliability - Document data processes, workflows, and systems for transparency and knowledge sharing - Troubleshoot and resolve data-related issues and provide support for data-related inquiries - Stay updated with the latest industry trends and best practices in data engineering and analytics - Ensure data security and compliance with relevant regulations and standards - Manage and prioritize multiple projects and tasks effectively to meet deadlines - Become Workato Automation Pro I, II, and III certified to create recipes facilitating data ingestion and auditing - Full-time telecommuting is an option Qualifications - Bachelor's degree (or foreign equivalent) in Computer Science, Business Analytics, Data Analytics, Information Systems, Statistics, Engineering, or related quantitative discipline - 2 years of experience in the job offered or a related occupation Requirements - SQL - dbt - Snowflake - Salesforce - Predictive Analysis - Data Governance - Relational Databases - CI/CD - Data Modeling - SchemaChange - Python - NetSuite - Must be legally authorized to work in the U.S. without sponsorship Benefits - Vibrant and dynamic work environment - Multitude of benefits for employees to enjoy inside and outside of their work lives
• Take ownership of meaningful metrics and data products, from definition through adoption. • Build and maintain dbt models that define how we measure the business. • Design and maintain dashboards used by growth, finance, and operations to make day-to-day decisions. • Improve data quality through testing, monitoring, and validation. • Enable self-serve analytics so teams can answer their own questions and move faster.
• dbt at Fora: project structure, conventions, CI/CD, tests, contracts, documentation, and performance. • Data models across bronze, silver, and gold layers. • The semantic layer (dbt MetricFlow or equivalent): metric definitions, dimensions, governance, and adoption. • Production operation of the transformation layer: jobs, dependencies, failures, retries, alerts, environments, and release hygiene. • Python tooling for validation, dbt utilities, lightweight automation, and integrations. • Data quality, test coverage, and observability for modeled tables. • Partnership with Risk & Analytics to formalize business metrics currently spread across SQL, Tableau, and analyst knowledge.
At Guild, we unlock opportunity for America’s workforce through education, skilling, and career mobility.
Role Description Guild is hiring an Analytics Engineer who will sit at the intersection of data, AI, infrastructure, and analytics, to help shape and deliver valuable data and business-critical reporting and insights for Guild. You will be responsible for organizing, standardizing, and analyzing our data to enable Guild’s Analytical efforts. This role will have a critical impact on the business and our students by surfacing valuable data and providing insight into opportunities for improvement across all aspects of our business. - Develop, maintain, and deeply understand core data models and curated datasets that support reporting, AI, and advanced analytics use cases, effectively communicating their structure and purpose to enable broad access to trusted data. - Develop a deep understanding of business and operational needs by building strong relationships across the teams who manage and use Guild’s data. - Perform in-depth data QA by diving into various data sources to identify and resolve issues. - Efficiently execute on assigned projects and requests from business partners, proactively communicating progress, timelines, and any challenges to manage stakeholder expectations for delivery. - Translate business questions into technical requirements as part of a well-defined development cycle. - Act as subject matter expert for Looker/Omni infrastructure and content, supporting team members in troubleshooting issues that arise. - Implement and maintain robust governance and oversight processes to ensure accuracy and continuity of critical data sources and reporting. Qualifications - 3+ years of full-time work experience as an analytics engineer, data analyst, BI analyst, data engineer or similar. - Experience designing, developing, and maintaining core data models that support a range of downstream use cases, including reporting, self-service analytics, and AI/ML applications. - Hands-on experience with modern data transformation frameworks (e.g., dbt or similar tools), including building scalable models, managing dependencies, and scheduling reliable data pipelines. - Strong understanding of data modeling best practices and modeling layers (e.g., staging, intermediate, marts), with a focus on maintainability, performance, and long-term extensibility of the analytics layer. - Hands-on experience with data model development and reporting in data visualization tools such as Looker, Omni or Tableau. Requirements - Highly skilled in SQL, and some experience in a scripting language (e.g. Python, R). - Demonstrated attention to detail and commitment to data quality and reporting accuracy. - Analytical, intellectually curious, creative problem-solver who is comfortable going beyond data access to analytics and strategic insights. - Keen design and data visualization skills – you know how to transform data to generate useful insights and be easily digestible. - In-depth understanding and application of Data Engineering standard processes. - Teammate approach, with strong interpersonal and influencing skills. - Passion for our mission – Guild is pioneering a new path for career development as a benefit in a complicated and regulated space – success means quickly and effectively adapting your expertise. Benefits - Access to low-cost, high-quality health care options through Collective Health and Kaiser (due to coverage limitations, Kaiser is currently only available in CA & CO). - Access to a 401k to help save for the future. - Vacation policy to rest and recharge. - 8 days of fully-paid sick leave, to take the time to heal and or recover. - Family-friendly benefits, including 12 weeks of parental leave for non-birthing parents and 18-20 weeks for birthing parents; 2-week ramp-up period for when employees return from a leave of 6 weeks or more; as well as employer-paid short-term and long-term disability, employer-sponsored life insurance, fertility and caregiving benefits. - Well-rounded wellness benefits including free and low cost mental health resources and financial wellbeing support services. - Education benefits and tuition assistance to help your future development and growth.
Role Description GameChanger is seeking a Senior Analytics Engineer to join the Analytics Hub team. Our mission is to deliver easy-to-use, extensible data models and self-serve capabilities that enable stakeholders across the company to answer data questions quickly and confidently. You’ll collaborate with Analytics, Data Engineering, and cross-functional partners in Finance, Product, and Engineering to scale the platforms that power decision-making, automation, and measurement. In this role, you will work with both first- and third-party data to architect and maintain the data foundation for reporting, analysis, and experimentation. Using Python, SQL, and DBT, you’ll transform warehouse data into scalable, self-serve data models and artifacts (e.g., metrics, dashboards) that unlock insights and empower teams across Finance, Product, and Engineering. What You’ll Do: - Own architecting, optimizing, and transforming finance and product centric data models in DBT for flexible analysis by Data Analysts / Scientists and self-service by business stakeholders. - Design data validations to ensure data integrity throughout our pipelines, and assure the accuracy of our reporting. - Create transparency throughout the full data pipeline by establishing foundational processes with upstream data producers and downstream data consuming tools (BI, Reverse ETL, experimentation). - Advance agentic tooling and other automation efforts that help the team spend less time investigating data issues, and more time doing analyses. - Apply software engineering best practices like version control and continuous integration to the analytics code base. - Work closely with our Data Engineers, Analysts, Data Scientists, Diamond (Baseball/Softball) Sports, and Finance teams to build foundational models around new sport specific features, monthly recurring revenue, and subscription forecasting. - Support cross functional core metrics and data dependencies with leadership visibility. Qualifications - 4+ years of experience in the Product, Finance, or Operations space as an analytics engineer, data analyst, data engineer, or equivalent. - Ability to write complex SQL, ad-hoc data pipelines, and experience in using Python for data analysis. - Hands-on experience implementing modern data modeling strategies with DBT, including validating data, building macros, and selecting optimal materialization. - Proven record of proactively driving improvements to data warehouse architecture. - Comfort with event tracking data and product analytics tools, including familiarity with common event data analyses like funnels and user paths. - Experience scaling a data platform’s capabilities while balancing warehouse costs. - Deep understanding of dimensional modeling techniques and building data for scale. - Comfort working in an agile, iterative environment and ability to thrive in a remote first organization. - Experience building and maintaining semantic layers and self-service technologies (e.g. dbt semantic views and LookML) for non-technical end-users. - Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations amongst cross-functional stakeholders. - Fluent in version control using git. Requirements - Direct work with the tools in our data tech stack: Airflow, Github Actions, AWS, Snowplow, Braze, Fivetran, DBT, Snowflake, BigQuery, Looker, Hex, Kubit, Statsig (or equivalents). - Comfortable productionizing agentic tooling and automating analytics workflows. - Significant modeling and architecture experience with web and app-based subscription data or front-end event-tracking data (e.g., Snowplow, Segment). - Experience optimizing query performance within a data lakehouse architecture and/or with materialized views. - Familiarity with creating common Software as a Service (SAAS) metrics. - Familiarity modeling data from low latency and real-time data pipelines. Benefits - Work remotely throughout the US* or from our well-furnished, modern office in Manhattan, NY. - Unlimited vacation policy. - Paid volunteer opportunities. - Technology stipend - $4,000 every 2 years after your start to make sure you have the latest and greatest technology. - WFH stipend - $500 annually to make your WFH situation comfortable. - Monthly physical, mental, wellness & learning stipend offered through Holisticly. - Monthly lifestyle stipend offered through Fringe. - Full health benefits - medical, dental, vision, prescription, FSA, HRA, HSA, and coverage for family/dependents. - Retirement savings - Traditional and Roth 401K plans are offered through Vanguard, with an immediate company match. - Life insurance - basic life, supplemental life, and dependent life. - Disability leave - short-term disability and long-term disability. - Company paid parental leave - up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents. - Family building benefits offered through Progyny. - DICK'S Sporting Goods and their family of brands teammate discount.
A leading global aerospace company and top U.S. exporter, Boeing develops, manufactures and services commercial airplanes, defense products and space systems for customers in more than 150 countries. Our U.S. and global workforce and supplier base drive innovation, economic opportunity, sustainability and community impact. Boeing is committed to fostering a culture based on our core values of safety, quality and integrity.
• Support the Data Integration and Analytics (DI&A) Team virtually • Focus on supporting Engineering & Technology Innovation business organization • Design and develop database systems to integrate data from numerous sources • Improve data quality and support clean and efficient data mining and management • Maintain database security architecture • Develop and map XML schema to support data import/export with Oracle database • SQL coding and PowerBI expertise • Establish related data tables, views, constraints, triggers, stored procedures, and functions using T-SQL and PL/SQL • Utilize PL/SQL and JavaScript within Oracle Application Express (APEX) • Understand complex data analysis and mining solutions
ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV) has applied innovation and user-designed, data-driven applications and solutions. We are building the most trusted and efficient digital marketplace with data solutions for sourcing, selling, and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of the industry and we want you to join us on our journey.
Role Description The Senior Analytics Engineer on the ACV Capital team is an expert practitioner who transforms raw data into trusted, decision-ready models and reports that drive the lending business forward. Sitting at the intersection of data engineering and business intelligence, this role owns the full analytics stack - from dbt model design and data quality to Omni BI dashboards - and partners directly with Capital leadership to surface insights on lead targeting, loan origination, account management, dealer servicing, and operational compliance. A key objective of this role is reducing ad-hoc analytical bottlenecks over time. You will be expected to answer urgent business questions quickly and directly, while systematically building the underlying dbt models, metric definitions, and BI layer in a way that enables self-serve analytics - including AI-assisted querying - so that Capital stakeholders can answer common questions themselves. Responsibilities - Analytics Modeling & Data Quality: - Design, build, and maintain dbt models (staging, intermediate, production layers) that serve as the single source of truth for Capital KPIs, with machine-readability in mind. - Enforce data quality through dbt tests, source freshness checks, and documentation so downstream consumers can trust what they see. - Write complex SQL transformations on large datasets; optimize for cost and performance. - Reporting & BI: - Translate business questions into well-scoped analytical requirements; define metrics in collaboration with Capital leadership and keep definitions governed in our semantic layer. - Build and own the Omni BI semantic layer, enabling self-serve chat and dealer-facing embedded reporting. - Balance responsiveness to ad-hoc requests while optimizing via building: triage what should be answered once vs. what should be codified so stakeholders or AI tools can self-serve it in the future. - Deliver clear, compelling data narratives to non-technical stakeholders; support follow-on questions and iterate quickly. - Capital Business Domains: - Lead Targeting: develop models and dashboards that identify high-propensity dealer and borrower segments to support outbound sales strategy. - Loan Origination Tracking: build funnel visibility from application through funding; surface bottlenecks and conversion opportunities. - Operational Functions: provide analytical support for account management workflows, dealer servicing SLAs, and audit/compliance reporting. - Project Ownership & Stakeholder Partnership: - Own analytical initiatives end-to-end: identify stakeholders, define scope and timelines, and execute without requiring close supervision. - Proactively surface opportunities and deliver data-driven recommendations — not just answers to questions that were asked. - Navigate competing priorities across multiple stakeholder groups; propose win-win solutions when technical requirements conflict. Qualifications - BA/BS in Statistics, Mathematics, Computer Science, Operations Research, or related. - Master's or Ph.D. a plus, but offset by demonstrated experience and a deep toolbox. Requirements - 5+ years of professional experience in analytics engineering, data engineering, or BI. - Hands-on production experience with dbt (model design, testing, documentation, incremental strategies). - Proficiency building semantic layers; Omni or Looker BI experience preferred, but similar experience considered. - Expert-level SQL; comfortable with window functions, complex joins, and query optimization in BigQuery or a comparable cloud warehouse. - Experience delivering major analytical initiatives independently, from scoping through stakeholder presentation. - Background in financial services, fintech, or lending is a meaningful plus - familiarity with origination, account management, or B2B lending workflows accelerates ramp. - Experience with Git-based version control workflows. Soft Skills - Communicates analytical findings clearly to non-technical audiences. - Comfortable navigating ambiguity. - Collaborative, low-ego, and invested in the team's collective output. - Strong instinct for knowing when to answer quickly vs. when to build properly. Nice-to-Haves - Experience with Google Cloud Platform. - Familiarity with AI-assisted analytics or developer workflows. - Exposure to credit risk, payment systems, or audit/compliance reporting contexts. Benefits - Multiple medical plans including a high deductible, low cost health plan. - Company-sponsored (paid) Short-Term Disability, Long-Term Disability, and Life Insurance. - Comprehensive optional benefits such as Dental, Vision, Supplemental Life/AD&D, Legal/ID Protection, and Accident and Critical Illness Insurance. - Generous paid time off options, including uncapped vacation days, the greater of 3 paid sick days or in accordance with the applicable state or local paid sick leave law, 6 paid company holidays, 2 floating holidays, parental leave, bereavement leave, jury duty leave, voting leave, and other forms of paid leave as required by applicable law or regulation. - Employee Stock Purchase Program with additional opportunities to earn stock in the Company. - Retirement planning through the Company’s 401(k).
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SQL, Python, ETL, Data Engineering, dbt, BigQuery