Top Remote Analytics Engineer Jobs

Architects and scales enterprise data models, dimensional models, dbt transformation pipelines, semantic layers, and BI datasets. The role focuses on data quality, testing, observability, governance, metric standardization, documentation, performance optimization, and secure access controls. It partners with executives and cross-functional teams, leads analytics engineering initiatives, troubleshoots complex data issues, owns domain models, and mentors engineers while advancing the company’s analytics platform strategy.

Own production-grade analytics pipelines from design through maintenance, build dbt-based analytical models using Kimball dimensional modeling, and deliver reliable data features. Partner with Product, Engineering, and Data Science teams to translate retail signals into business insights. Establish standards for monitoring, documentation, reproducibility, and code quality. Use AI tools to accelerate development and prototype conversational data experiences for natural-language retail data exploration.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

The Analytics Engineer will design and implement analytics solutions, maintain reporting dashboards, partner with Product on KPIs, and support marketing with analytics.

Design, build, and operate production-grade AI tools, automations, and integrations for HR workflows. Lead LLM-based solutions (prompting, RAG), integrate people systems (Workday, Slack, Google Suite), improve data quality, support end users, and drive measurable productivity and product roadmap decisions.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

Design, build, and maintain end-to-end data models and pipelines to support CX operations, compliance reporting, and customer insights. Create dashboards and metrics, enforce data quality and governance, automate recurring workflows, and partner with stakeholders and broader data teams to deliver self-serve analytics solutions.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.

As a Billing & Analytics Software Engineer, you'll design and maintain the billing pipeline, integrate billing systems, and develop customer-facing analytics dashboards to support revenue recognition and operational observability.

Leads data and analytics engineering for Zero Trust maturity assessment and implementation measurement. Designs common data models, integrates and validates enterprise data, develops maturity and risk metrics, supports prioritization and gap analysis, and establishes data quality, lineage, traceability, and documentation practices. Partners with dashboard and automation specialists to streamline reporting and data refresh workflows.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.

Own and evolve Afresh’s analytics platform, including data architecture, dimensional models, semantic-layer metrics, pipelines, data quality, governance, and AI-assisted analytics tooling. Collaborate with data, product, engineering, and operations teams to support internal and customer-facing data products. Lead high-impact projects, optimize billion-row datasets, establish reliable analytics practices, and mentor other engineers.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.

Design and implement end-to-end Microsoft Fabric data solutions (ingestion, Lakehouse, warehouse, real-time). Create architectures, reusable frameworks, and governance patterns for insurance datasets. Lead ingestion pipelines, optimize performance/cost, integrate with Azure services and security, support regulatory compliance, and provide technical direction to engineering and analytics teams.

Own and evolve the analytics platform, including data models, pipelines, metric definitions, semantic layers, dashboards, and self-service data products. Partner with cross-functional stakeholders to translate business needs into reliable technical solutions. Lead data initiatives, improve ELT reliability and governance, resolve quality issues, mentor teammates, and shape the Analytics team’s technical roadmap. The role requires strong SQL, dbt, modern data-stack experience, business communication, and independent execution in an ambiguous environment.

Leads enterprise analytical modeling and semantic architecture, establishes standards for testing, documentation, governance, lineage, observability, and access, and develops reusable governed data products. Partners across Product, Engineering, Finance, Clinical, Research, Marketing, and AI teams; guides architecture reviews, data quality ownership, semantic layer design, and governance adoption. Mentors engineers and drives modernization of analytical environments.

Partner with Product Discovery & Promotion to build scalable analytics for Live content and new formats: develop metrics, analyses, dashboards, and data models; source data with data engineers; and act as a thought partner driving analytic solutions and stakeholder decision-making.

Build and operate reliable ETL and ELT pipelines across lakehouse and transactional systems. Develop data models, enforce governance, integrate diverse data sources, and support analytics, APIs, and predictive tools. Monitor performance, data quality, lineage, cost, and uptime while collaborating with data science, AI, product, and innovation teams.

Develop and maintain enterprise HCM analytics, dashboards, compliance reports, semantic layers, data extracts, and predictive workforce insights using Oracle Fusion technologies. Translate agency requirements into reporting solutions, support data migration and onboarding, ensure accessibility compliance, and provide technical leadership and mentoring across a federal HCM modernization initiative.

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

Own and scale client-facing data transformation pipelines for financial and operational data. Build reliable analytical models, data integrity tests, and integrations across diverse sources. Partner with Customer Success and Engineering to troubleshoot data issues, optimize critical pipelines, establish engineering standards, and improve developer experience. Use dbt, SQL, Python, BigQuery, and AI-enabled workflows to deliver performant, well-documented FP&A data products while mentoring teammates and contributing to hiring and onboarding.

Develop and architect Oracle HCM analytics solutions, including OTBI and BI Publisher reports, OAC dashboards, predictive analytics, HCM Extracts, semantic models, and workforce visualizations. Support federal HR compliance reporting, accessibility standards, agency onboarding, historical data migration, training, and self-service analytics. Lead technical workstreams, review deliverables, solve complex reporting challenges, and mentor junior team members.

Develop and maintain Oracle HCM analytics and reporting solutions for a federal modernization program. Build OTBI and BI Publisher reports, OAC dashboards, HCM Extracts, executive visualizations, compliance submissions, predictive analytics, and accessible 508/WCAG-compliant outputs. Collaborate with HR functional teams, support data transitions and reporting templates, and provide analytics training. The role requires extensive enterprise BI experience, SQL proficiency, workforce metrics knowledge, and familiarity with Oracle Fusion HCM and federal HR reporting.

Build and maintain production dbt models on Databricks as the organizations source of truth. Ensure data quality via testing, CI/CD, and documentation. Create Databricks dashboards and semantic metrics, support external reporting, and partner with engineering and analytics teams to turn business problems into durable data products. Drive AI-native workflows using tools like Cursor and Claude Code.