Senior Data Engineer - Analytics

Responsibilities

• Design, develop, and maintain 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 machine learning 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; integrate 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.

Requirements

• 3+ years of experience in analytics engineering, data engineering, or a related role building analytics pipelines and data models.
• Experience working with Healthcare Claims Data.
• 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.
• Work authorization: Must be currently authorized to work in the United States without the need for sponsorship for a non-immigrant visa.

Technologies

• dbt Core
• SQL
• BigQuery
• Python
• Google Cloud Platform (GCP)
• Cloud Run
• Vertex AI
• FastAPI
• LLM APIs
• RESTful APIs