Senior Data Engineer - Analytics

Senior Data Engineer, AnalyticsLocation:

100% RemotePosition OverviewWe are seeking an experienced Analytics Engineer to join our data team and build reliable, scalable analytics infrastructure that turns data into actionable insights. The role is focused on designing and implementing data models, transformation pipelines, and APIs that power dashboards, ML features, and downstream systems. You will work closely with data scientists, analysts, and engineers to standardize metrics, improve data quality, and enable self-service analytics across the organization.

Key ResponsibilitiesDesign, develop, and maintain robust ELT/ETL data transformation pipelines using dbt Core and SQL targeting BigQuery.

Author modular, tested SQL models and Python-based data transformations to support analytics, reporting, and ML feature generation.

Implement data quality checks, lineage, and observability to ensure reliable analytics outputs and SLAs.

Collaborate with product, analytics, and ML teams to define metric definitions and translate business requirements into performant data models.

Build and maintain RESTful APIs and integrations to surface curated datasets and features for internal and external consumers; implement and consume LLM APIs where applicable.

Deploy and monitor data services and lightweight API endpoints on GCP, leveraging Cloud Run and other serverless infrastructure when appropriate.

Optimize performance and cost for BigQuery workloads through partitioning, clustering, and query tuning.

Document data models, transformation logic, and operational runbooks; mentor teammates on best practices for dbt, SQL, and analytics engineering.

Qualifications3+ years of experience in analytics engineering, data engineering, or a related role building analytics pipelines and data models.

Expert proficiency in SQL and strong experience with Python for data transformation, orchestration, or testing.

Proven experience using dbt Core to build modular, tested analytics transformations and manage deployments.

Solid experience with Google Cloud Platform, especially BigQuery, including query optimization and cost management.

Experience building and integrating APIs; familiarity with LLM APIs and integrating large language model outputs into analytics or product workflows.

Strong understanding of data modeling concepts, ETL/ELT patterns, data quality practices, and observability.

Excellent communication skills and ability to collaborate across cross-functional teams to operationalize analytics.

Nice to have: hands-on experience with Cloud Run, Vertex AI, and FastAPI for serving data or ML features; domain knowledge of healthcare claims and related data models.