Top Remote Analytics Engineer Jobs

Build and own commercial data models in Snowflake and dbt for ARR, bookings, pipeline, account scoring, ICP fit, upsell, and whitespace analysis. Establish semantic layers, governance, documentation, testing, monitoring, and CI/CD practices. Partner with Sales, Marketing, Finance, and enterprise data teams to deliver trusted self-service analytics, improve data infrastructure, and develop AI-powered automation. This senior individual contributor will own the roadmap and mentor analysts on data modeling and dbt.

Build scalable data pipelines, dimensional data marts, and reusable data products for analytics, automation, and AI-powered workflows. Partner with Data Science, Product, Engineering, and Operations to support self-service analytics, data governance, quality, security, and analytics engineering standards. Develop agentic tools, promote dimensional modeling, and deliver well-tested, documented data solutions that support experimentation and the company’s banking initiatives.

Own Hercules’ full data stack, including ETL from third-party providers into BigQuery, data modeling with dbt and medallion architecture, semantic-layer metric definition, and self-service business intelligence in Omni. Build reliable, maintainable systems and dashboards while applying strong software architecture, API design, code quality, and AI-assisted development practices.

Own product analytics and growth measurement by partnering with product and design, defining metrics and event tracking, building dbt models and data pipelines, creating dashboards, and analyzing activation, engagement, retention, funnels, cohorts, and experiments. Establish trustworthy product data standards, identify product-market-fit indicators, surface insights, and influence roadmap decisions while collaborating with clinical and research analytics teams.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Provide senior-level data engineering for analytics: resolve complex technical issues, build decision-support reports and dashboards, lead projects, prepare and integrate data, coach staff, and ensure high-quality analytics to support academic, research, and healthcare goals.

Designs and maintains healthcare analytics infrastructure, production data models, semantic layers, and transformation pipelines using advanced SQL and analytics engineering practices. Integrates payer claims, EMR, clinical, attribution, quality, and operational data. Performs ad hoc analysis, defines standardized healthcare metrics, validates data quality, optimizes queries, documents data flows, and partners with clinical, operational, IT, and payer stakeholders to support value-based care and enterprise reporting.

Leads analytics engineering and analytics-ready data architecture for government clients. Designs standardized data models, transformation logic, validation frameworks, and reusable integration patterns. Governs data quality, QA, backfills, and release processes while resolving complex data issues. Integrates web, email, social, survey, and client-system data to support dashboards, reporting, measurement, and insights. Advises stakeholders, influences enterprise standards, coordinates with product teams, and supports client-facing analytics workstreams.

Partners with product, business, content operations, and data teams to define measurement frameworks, analyze media production workflows, build prototypes and dashboards, strengthen data models, and provide data-driven insights for strategic decisions. The role focuses on measuring GenAI-enabled production improvements, operational efficiency, creative flexibility, and innovation impact while influencing stakeholders and leadership.

Designs scalable data models, optimized SQL queries, analytics infrastructure, semantic layers, and data applications. Partners with data science, product, engineering, and business teams to enable dashboards, self-service analytics, reporting, and enterprise data-driven decision-making. The role also establishes analytics engineering best practices, improves developer experience, and supports secure, compliant data warehousing.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, cloud data infrastructure, and complex data models. Supports analytics partners, develops data warehouse solutions, tunes SQL and database performance, troubleshoots production issues, and delivers end-to-end data engineering projects. The role collaborates with architects, analysts, developers, and business stakeholders, applies big data technologies, supports agile delivery, and mentors team members.

Build user-facing reports, data models, and pipelines in BigQuery; apply statistical analysis to generate insights; troubleshoot analytics stack issues; review schemas and code; collaborate with product and engineering teams; and use AI agents to automate workflows and surface insights. The role requires strong SQL, BigQuery, Looker, Python, data warehousing, statistics, communication, and product judgment.

Designs, builds, validates, and maintains governed analytical data models, curated datasets, and reporting layers. Translates business requirements into data mappings, transformation logic, and reusable BI datasets. Develops SQL and dbt tests, performs data reconciliation and root-cause analysis, optimizes Snowflake models, and supports dashboards, reports, UAT, and regulatory extracts. Collaborates with stakeholders, data engineers, architects, analysts, and business teams across insurance and corporate functions.

Develop, administer, and support Power BI, Azure, Fabric, and cloud analytics solutions. Build semantic models, reports, dashboards, database objects, and automation; monitor platform capacity, performance, reliability, and costs. Partner with engineering, business, and project teams to define requirements, deliver projects, support users, and improve BI operations. Establish standards and best practices in an Agile/Scrum environment while enabling scalable, AI-supported analytics solutions.

Own Bridge’s data function by building reliable pipelines, ETL orchestration, dbt models, marts, data products, dashboards, alerts, and self-service analytics. Investigate ambiguous business questions, improve data quality, structure business context for AI systems, and develop AI-powered tools and evaluations. The role also requires documentation, testing, code review, training, and cross-functional support.

Lead architecture, systems, and roadmap for Coinbase's Compliance Reporting Data Platform. Design and build production-grade data models, pipelines, quality frameworks, validations, and certification processes. Establish data contracts, monitoring, reconciliation, and audit-ready processes. Partner with engineering and compliance stakeholders, respond to regulatory exams, and mentor engineers while shaping standards and documentation.

Owns analytics datasets and data products for Netflix’s cloud games infrastructure. Builds scalable pipelines, data models, metrics, dashboards, tooling, and self-service assets from massive telemetry data. Partners with infrastructure engineering, data engineering, and data science teams to improve quality of experience, capacity, and utilization insights. Responsibilities include telemetry and logging, visualization, trustworthy documentation, scalable data solutions, and independently prioritizing high-impact investments.

Leads end-to-end development of an AWS-based healthcare analytics platform across frontend, backend, data infrastructure, and AI capabilities. Sets architecture and engineering standards, writes and reviews code, mentors engineers, and partners with product, data engineering, and data science teams. Develops ETL pipelines, production machine learning services, generative AI features, and scalable analytics products while maintaining security, governance, privacy, and healthcare data quality standards.

Leads scalable data model and pipeline design, dbt development, testing, CI/CD, and analytics engineering implementations. Partners with analysts, engineers, and stakeholders to translate business needs into reliable models and semantic layers. Advises on data architecture, governance, quality, performance, and long-term scalability while mentoring peers and contributing to shared tooling, standards, and frameworks.

Design and develop scalable analytics tools, dashboards, evaluation frameworks, and observability systems for promotional media and marketing workflows. Partner with machine learning engineers, data scientists, product managers, and business stakeholders to monitor algorithm adoption, pipeline health, performance drift, and SLA adherence. Translate ambiguous creative and quality requirements into measurable objectives, improve recommendation and asset-generation models, and use data insights to guide business decisions.

Build and maintain invoicing, reimbursement, revenue recognition, claims, and financial reporting models using SQL and dbt. Reconcile merchant, operational, warehouse, and accounting data; investigate variances; validate expenses; and establish automated financial controls. The role also triages data issues, investigates production APIs, supports audits, partners on merchant configuration, and drives upstream fixes through root-cause analysis and automation.

Lead complex customer analytics engagements, translating industrial business needs into scalable analytics architectures and solutions. Advise customers, drive product adoption, identify high-value use cases, mentor Analytics Engineers, resolve technical escalations, and influence product roadmaps. Apply expertise in industrial process data and sectors such as power, pharmaceuticals, and semiconductors. Collaborate with customers, partners, product teams, and account teams to deliver measurable business outcomes.

Build and maintain a regulatory reporting data platform using SQL and dbt, including models, automated validations, data pipelines, and testing. Investigate data issues end to end, validate submissions, support audits and legal data requests, monitor upstream changes, collaborate with product, engineering, compliance, and leadership, and participate in on-call coverage. WOOF WOOF

Build scalable data foundations, analytics tooling, analysis pipelines, and trusted self-service datasets for product and data science teams. The role focuses on instrumentation, experimentation standards, data quality, metric governance, documentation, workflow orchestration, and cross-functional collaboration. Engineers will use SQL, Python or R, and AI-assisted workflows while validating results and protecting sensitive data.