Analytics Engineer Remote Jobs in California (US)
This page tracks remote analytics engineer openings that are location-eligible for California.
This page tracks remote analytics engineer openings that are location-eligible for California.
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552
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$81,499 - $159,000
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552 Jobs
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We make consumer technology products for families: Skylight Frame & Skylight Calendar
Role Description We are expanding our Data team and are in need of a rigorous Senior Analytics Engineer to partner closely with our Finance and Operations teams. This role will own the Finance/Operations data layer, bring new data into our warehouse from systems like NetSuite, Ramp, and Pigment, and build the dashboards and metrics leadership relies on to run the business. - Stakeholder Collaboration: Partner with Finance, Operations, and the rest of the Data team to understand business processes and source-system workflows, define pipeline requirements, and identify data gaps and downstream reporting impacts. - Data Infrastructure: Own the Finance and Operations data layer and build trusted, reusable data models that support reporting, analysis, and decision-making. - Data Integration: Design and document how data should flow between source systems such as NetSuite, Ramp, and Pigment into Snowflake and Omni. - Data Quality: Create validation checks, reconciliation workflows, and exception reporting to improve trust in critical Finance/Ops data across source systems, Snowflake, and Omni. - Metric Governance: Define and govern key Finance/Operations metrics with business owners, including business logic, data grain, source of truth, ownership, refresh cadence, and known limitations. - Dashboard Development: Create and maintain dashboards, from executive-level summaries to granular self-serve analytics, to communicate performance metrics and support root-cause analysis. - Continuous Improvement: Identify and execute opportunities to automate manual data flows, reporting processes, and reconciliation workflows. Qualifications - 5+ years in an analytics role with exposure to financial or operational data sets. - Strong SQL skills and experience building reusable, well-structured data models in a cloud data warehouse environment, ideally Snowflake. - Experience with BI or semantic-layer tools such as Omni, Looker, Tableau, Power BI, or Sigma. - Experience validating outputs, reconciling discrepancies, documenting assumptions, and creating checks for critical metrics. - Ability to understand business processes and translate them into data models, metrics, dashboards, and documentation. - Strong stakeholder management skills, including gathering requirements, managing expectations, pushing back constructively, and communicating tradeoffs. - Comfort working in an early-stage or evolving data environment where systems, pipelines, definitions, and ownership boundaries may still be forming. Requirements - Experience with source-of-truth systems such as ERP (NetSuite), WMS, TMS (OSCA), or CPM (Pigment). - Experience with wholesalers and EDI. Benefits - Competitive Salary + Equity Package - 401K matching - Wellness, learning, and home-office budgets - Health, Dental & Vision Medical Plans - Tremendous autonomy to set the direction of your work - Unlimited PTO - Company holidays on the first Friday of every month (Excluding November, December, and January)
Founded in 1969, ICF is a global advisory and technology services company headquartered in Reston, Virginia. It delivers data-driven solutions across energy, en
Role Description ICF is seeking a Senior Climate Analytics Specialist with strong scientific programming and cloud-based, big data experience to support our broad portfolio of work on climate risk and resilience. Our projects span across commercial clients and all levels of government, enhancing the resilience of energy, transportation, and other critical infrastructure systems, and the vital societal and natural elements that make our communities whole. Our climate risk analytics leverage rigorous science, machine learning, distributed computing, and provide clear communication to enable proactive planning and implementation of resilience solutions. The consultant chosen for this position will apply advanced analytics to the analysis and interpretation of weather and climate data, contribute to the development of climate risk tools and products, and support multi-disciplinary teams on multiple short- and long-term projects. This role is ideal for candidates interested in applying advanced analytics and machine learning to novel, high-impact problems where traditional modeling approaches are insufficient and new methods must be developed. What you’ll be doing… - Serve as a technical expert on multi-disciplinary teams focused on applied climate risk and resilience projects - Use scientific programming, cloud-based distributed computing, and large-scale geospatial data processing to advance climate analytics and products - Translate complex climate risk questions into tractable analytical and modeling frameworks, selecting appropriate statistical, machine learning, and physics-informed approaches - Design, train, and rigorously validate machine learning and statistical models in data-limited and non-stationary climate contexts - Interface with clients on climate risk and resilience topics, and prepare high-quality communication materials such as presentations and reports - Complete tasks in fast-paced and self-motivated environment in a timely and efficient manner Qualifications - Bachelor's Degree in climate science, atmospheric science, Earth science, data science, meteorology, or similar - 5+ years of relevant experience applying advanced analytics to climate, geospatial, or environmental data - 2+ years of experience with Python for processing and analyzing large, multidimensional datasets (e.g., NetCDF, Zarr), including use of Pangeo ecosystem tools such as Xarray and Dask - Demonstrated experience designing and implementing scalable, cloud-based workflows for large geospatial and climate datasets, including parallel processing, memory-aware computation, and reproducible pipelines (e.g., AWS, SageMaker) - Demonstrated experience applying machine learning and statistical models to climate science, risk analysis, or related topics, using relevant Python packages (e.g., scikit-learn, PyTorch, etc.) Requirements - Advanced degree in climate science, atmospheric science, Earth science, data science, meteorology, or similar - Ability to perform self-directed analytical work related to climate science topics and physical climate risk pertaining to energy systems, transportation networks, or other sectors - Experience working with extreme events, tail risks, or rare-event modeling in environmental or geospatial contexts - Outstanding oral and written communication skills; ability to communicate complex climate information to non-scientists to inform decision-making - Experience working with and leading multi-disciplinary teams - Organized, detail oriented, and the ability to prioritize and multi-task Benefits - Flexible workplace arrangements, work-life balance - Donation matching, volunteer opportunities - Tuition reimbursement, access to professional development resources, 401k matching, Employee Stock Purchase Plan - And many, many more (Ask your recruiter for more details!)
Founded in 1969, ICF is a global advisory and technology services company headquartered in Reston, Virginia. It delivers data-driven solutions across energy, en
Role Description ICF is seeking a Senior Climate Analytics Specialist with strong scientific programming and cloud-based, big data experience to support our broad portfolio of work on climate risk and resilience. Our projects span across commercial clients and all levels of government, enhancing the resilience of energy, transportation, and other critical infrastructure systems, and the vital societal and natural elements that make our communities whole. Our climate risk analytics leverage rigorous science, machine learning, distributed computing, and provide clear communication to enable proactive planning and implementation of resilience solutions. The consultant chosen for this position will apply advanced analytics to the analysis and interpretation of weather and climate data, contribute to the development of climate risk tools and products, and support multi-disciplinary teams on multiple short- and long-term projects. This role is ideal for candidates interested in applying advanced analytics and machine learning to novel, high-impact problems where traditional modeling approaches are insufficient and new methods must be developed. The preferred locations for this position are Salt Lake City, New York City, or Crystal City, VA. Responsibilities - Serve as a technical expert on multi-disciplinary teams focused on applied climate risk and resilience projects. - Use scientific programming, cloud-based distributed computing, and large-scale geospatial data processing to advance climate analytics and products. - Translate complex climate risk questions into tractable analytical and modeling frameworks, selecting appropriate statistical, machine learning, and physics-informed approaches. - Design, train, and rigorously validate machine learning and statistical models in data-limited and non-stationary climate contexts. - Interface with clients on climate risk and resilience topics, and prepare high-quality communication materials such as presentations and reports. - Complete tasks in fast-paced and self-motivated environment in a timely and efficient manner. Qualifications - Bachelor's Degree in climate science, atmospheric science, Earth science, data science, meteorology, or similar. - 5+ years of relevant experience applying advanced analytics to climate, geospatial, or environmental data. - 2+ years of experience with Python for processing and analyzing large, multidimensional datasets (e.g., NetCDF, Zarr), including use of Pangeo ecosystem tools such as Xarray and Dask. - Demonstrated experience designing and implementing scalable, cloud-based workflows for large geospatial and climate datasets, including parallel processing, memory-aware computation, and reproducible pipelines (e.g., AWS, SageMaker). - Demonstrated experience applying machine learning and statistical models to climate science, risk analysis, or related topics, using relevant Python packages (e.g., scikit-learn, PyTorch, etc.). Preferred Skills/Experience - Advanced degree in climate science, atmospheric science, Earth science, data science, meteorology, or similar. - Ability to perform self-directed analytical work related to climate science topics and physical climate risk pertaining to energy systems, transportation networks, or other sectors. - Experience working with extreme events, tail risks, or rare-event modeling in environmental or geospatial contexts. - Outstanding oral and written communication skills; ability to communicate complex climate information to non-scientists to inform decision-making. - Experience working with and leading multi-disciplinary teams. - Organized, detail oriented, and the ability to prioritize and multi-task. Benefits - Flexible workplace arrangements, work-life balance. - Donation matching, volunteer opportunities. - Tuition reimbursement, access to professional development resources, 401k matching, Employee Stock Purchase Plan. - And many, many more (Ask your recruiter for more details!). Pay Range The pay range for this position based on full-time employment is: $81,499.00 - $138,549.00.
• Work at the intersection of data engineering and analytics, partnering with analysts and stakeholders across the business to turn raw data into trusted, reusable datasets. • Model data from a broad ecosystem of sources on our central data platform. • Help define and validate key metrics, ensuring the data our models, dashboards, and AI tools depend on is accurate, reliable, and well documented. • Contribute to semantic layer and metric governance, ensuring definitions are consistent, documented, and reliable across reporting surfaces. • Mentor junior and intermediate analytics engineers through code review, pairing, and knowledge sharing.
Turning sustainability goals into reality with renewable natural gas (RNG) for transportation.
• Design, develop, and support artificial intelligence, intelligent automation, data engineering, analytics, and operational intelligence solutions across Clean Energy Fuels. • work across the full solution lifecycle—from business requirements and architecture through development, deployment, and support
Role Description We’re hiring a GTM Analytics Lead to act as a strategic lever across our go-to-market engine. This is a hands-on IC role focused on driving decisions, not just reporting. You’ll refine how we measure performance, uncover what’s actually driving revenue, and surface insights that directly impact how we allocate spend, scale channels, and operate GTM. You will sit at the intersection of Marketing, Sales, and Finance, turning real-time data into action and helping us grow fast while maintaining high-quality, sustainable revenue. Responsibilities - Drive GTM Performance Through Data - Own and refine how we measure performance across marketing, pipeline, and revenue - Turn data into clear recommendations on where to invest, what to cut, and how to scale - Act as a strategic partner to GTM leaders on channel strategy and performance - Ensure growth is not just fast, but efficient and sustainable (strong conversion, healthy CAC, durable revenue) - Channel Discovery & Optimization - Identify new acquisition channels and opportunities to drive incremental pipeline - Deeply analyze existing channels (paid, outbound, partnerships, organic) to improve efficiency and output - Separate signal from noise — understand what is actually driving pipeline and revenue vs what looks good on paper - Evaluate incrementality and ROI across all GTM spend to ensure scalable, repeatable growth - Marketing → Sales → Revenue Connectivity - Tie marketing activity directly to sales outcomes (conversion, velocity, ACV, win rates) - Identify friction points across the funnel and quantify impact - Build views that reflect real sales cycles (not artificial month-based reporting) - Highlight where growth is coming from high-quality vs. low-quality pipeline - Real-Time GTM Insights - Build and maintain reporting that gives teams real-time visibility into performance - Enable faster decision-making across Marketing, Sales, and Leadership - Move the org from lagging indicators → leading indicators - Surface early signals on pipeline quality, conversion risk, and revenue durability - GTM Data & Tooling Ownership - Work across the full GTM stack to ensure data is usable, connected, and actionable: - CRM: HubSpot / Salesforce - Sales tools: Nooks, Unify, Gong - Marketing tools + attribution systems - Data stack: Snowflake, dbt, BI tools (Omni, Looker, etc.) - Build and refine datasets that power GTM reporting (pipeline, attribution, channel performance) - Experimentation & Insight Generation - Partner with Growth and Marketing to analyze experiments and campaigns - Build frameworks to quickly evaluate what’s working and what’s not - Continuously surface insights that drive iteration and improvement - Ensure experiments lead to scalable wins, not one-off spikes Qualifications - 7–10+ years in analytics, growth analytics, or data roles - Experience owning or standing up GTM / growth analytics in a high-growth SaaS environment - Strong exposure to marketing + sales data and full-funnel analysis - Strong SQL and data modeling experience (non-negotiable) - Experience building datasets and working in modern data stacks (dbt, Snowflake, etc.) - Comfortable working across messy, imperfect data environments - Deep understanding of how SaaS GTM works end-to-end - Strong intuition around channels, pipeline generation, and revenue drivers - Ability to tie analysis directly to revenue quality, not just volume - You don’t just report — you push decisions - You focus on impact, not dashboards - You know how to prioritize what actually moves revenue - You care about building a durable growth engine, not short-term wins - Can translate complex data into simple, actionable insights - Comfortable working directly with execs and influencing GTM strategy Benefits - Embrace autonomy and accountability in a flexible work environment; we focus on outcomes and empower you to determine how to get the job done - Access our company-paid group benefits for you and your family, with $1,000 towards mental health support - Disconnect during our holiday closure and take advantage of our generous time off policies throughout the year - Enjoy monthly paid meals, an annual wellness allowance to support your well-being and parental leave top-ups as your family grows - Secure your stake in our success; you’ll receive competitive stock option grants as a pivotal early employee
Reimagining pharmacy management to provide the same care we would want for our loved ones
Role Description The Senior Analytics Engineer is an integral member of the data analytics organization and is responsible for managing, optimizing, overseeing and monitoring the retrieval, storage and distribution of large data sets to enable data-driven business processes and deliver actionable business insights through dashboards, reports and other self-service visualizations tools. Manages complex projects, mentors junior engineers, and ensures that engineering principles are applied consistently within the team. - Develops, constructs, tests and maintains data architecture, extract, load, transform (ELT) processes, logical and physical data models, data marts, meta data repositories and data warehouse designs in alignment with business requirements. - Optimizes data retrieval, develops data set processes, algorithms and identifies ways to improve data reliability, efficiency and quality. - Contributes to and maintains business glossary and other resources that foster cross-functional collaboration on analytical data resources. - Collaborates with business stakeholders to identify needs and opportunities for improved delivery, business processes and tasks that can be automated, and to understand the underlying data resources and their relationship to deliver actionable data driven insights and decision support. - Provides technical guidance to the analytics function and projects, ensuring that new initiatives enable effective analytic information management; builds and tests proof of concepts to test and demonstrate business value. - Cross-trains, supports, and works closely with team members in the following roles: Data Scientist, Systems Analyst, Report Developer. - Other duties as assigned. Qualifications - Bachelor’s degree in computer science, applied mathematics, engineering or another IT-related field; or equivalent combination of education and/or relevant work experience; High school diploma from an accredited school or equivalent GED. - 5 years of experience in IT, to include 3 years data analytics engineering and experience in business intelligence, data warehousing, or analytics. - Must be eligible to work in the United States without the need for work visa or residency sponsorship. Requirements - Demonstrated ability to architect, develop and maintain cloud technologies. - Understanding of relational and dimensional modeling to facilitate data wrangling, code operationalization and exploration of data. - Ability to develop, maintain, review and translate data models. - Proficient in SQL, procedures, and ELT implementations and experience with Cloud databases. - Owns delivery of moderately complex analytics engineering solutions end-to-end, including design, development, testing, and deployment. - Mentors and develops junior analytics engineers, providing guidance on best practices, code quality, and solution design. - Ensures adherence to data engineering standards, testing practices, and performance optimization across work products. - Understanding of Pharmacy Benefit Management / Healthcare eco system. Preferred Qualifications - DBT certified or equivalent work experience. - Experience with development tools such as GitHub and Jira. - Experience working with end users to gather requirements and build technical solutions from concept to implementation. - Programming experience in computer languages such as Python and R. - Experience with cloud database platforms and associated tools such as GCP (Google Cloud Platform) and Big Query. - Experience building and maintaining data and analytics systems/products using common BI tools and Cloud products. Benefits Potential pay for this position ranges from $108,000.00 - $184,000.00 based on experience and skills. To review our Benefits, Incentives and Additional Compensation, visit our Benefits Page and click on the "Benefits at a glance" button for more detail. Company Description Prime Therapeutics LLC is proud to be an equal opportunity and affirmative action employer. We encourage diverse candidates to apply, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sex (including pregnancy), national origin, disability, age, veteran status, or any other legally protected class under federal, state, or local law. We welcome people of different backgrounds, experiences, abilities, and perspectives including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law. Prime Therapeutics LLC is a Tobacco-Free Workplace employer. Positions will be posted for a minimum of five consecutive workdays.
FICO is an analytics company helping businesses make better decisions that drive higher levels of growth and success.
• Perform hands-on analysis, technical design, data modeling, development, testing, and deployment of Snowflake-based data solutions. • Own the end-to-end lifecycle of analytics data products, from raw ingestion through dbt transformation to semantic models consumed by AI agents and BI tools. • Design, build, and maintain dbt models, tests, and CI/CD pipelines for enterprise BI and analytics use cases. • Build and publish semantic models (Snowflake semantic views) that make enterprise data consumable by AI agents, BI tools, and business users, without requiring SQL. • Own Snowflake platform responsibilities including data architecture, query optimization, RBAC design, cost management, and warehouse administration. • Develop dashboards and analytics deliverables using modern visualization tools (Sigma, Power BI, Streamlit, or similar). • Partner with multiple cross-department business stakeholders and internal IT colleagues to translate business questions into data products, reports, dashboards, semantic models, or agent-queryable datasets. • Troubleshoot and ensure timely resolution of production data issues and platform defects. • Identify and apply creative and innovative approaches to resolving data modeling, integration, and delivery challenges. • Follow and support established processes for enhancements and change requests, as well as recommend and enforce coding standards. • Prepare and document technical designs and conduct code reviews and checkpoint meetings as needed. • Support and mentor junior team members through code reviews, pairing, and technical guidance. • Effectively communicate within the technical team and with business partners.
We empower the restaurant community to delight guests, do what they love, and thrive.
• Collaborate with domain teams to implement a hub & spoke data architecture • Develop the core Analytics layer in our data warehouse that serves as the hub • Build an AI-ready semantic layer that is extendable across business domains • Partner with business stakeholders and our product team to understand their data analytics needs • Work closely with the data engineering team to ensure scalability across the platform • Provide technical mentorship and leadership to team members
Role Description As a Data Analytics Engineer for GFiber, you will be working with multiple stakeholders across the organization to provide quantitative support, define metric rules and logic, deliver useful tables and reports, model business scenarios, and solve a wide range of business problems. To do so, you will be expected to create new pipelines from scratch, merging broad financial and ERP data sets together into a cohesive technical infrastructure. You will be responsible for engineering foundational table resources using Google Cloud Platform (GCP): BigQuery, Dataform, LookML, Dataplex, etc. The pipelines, metrics, tools, and analyses you develop will be used by our leaders to make strategic decisions and serve as a key input in decision-making. - Create foundational pipelines and data extractions with large data sets using SQL and other GCP technologies demonstrating comfort with software-engineering-level best practices and approaches to data pipelines and management. - Work with large, complex data sets to solve difficult analysis problems, assess the impact of initiatives, and create ongoing tooling/resources to run the business. - Collaborate with cross-functional partners to understand business context for solutions, analysis, and tooling needed to become the single point of contact for all financial data engineering questions. - Undertake specific tasks, bugs, and maintenance work. Additionally, own complex projects, proving mastery through accuracy, timeliness, and volume of work, with minimal guidance. Qualifications - Bachelor's degree or equivalent practical experience. - 5 years of experience in analytics, data science, and/or computer science engineering. - 5 years of experience with using SQL, writing queries from scratch on a daily basis, data engineering, architecture, pipeline management, and Extract, Transform, Load (ETL). - Expertise using GCP tools. Requirements - Experience in HTML, Python, or other coding languages. - Experience using data to identify opportunities for business improvement and defining/measuring the success of those initiatives. - Ability to use written and verbal communication to build relationships with cross-functional partners and conduct presentations for stakeholders, including executive leadership. - Ability to engage with PMO teams to prioritize, provide level of effort estimations, manage bug queues and bandwidth. Benefits - The US base salary range for this full-time position is between $105,600 - $154,900 + bonus + benefits. - As pay varies by location, your recruiter will share more about the specific salary range for your targeted location during the hiring process.
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SQL, Python, BigQuery, Snowflake, Looker, Tableau