Everforth is seeking a Senior Data Engineer - Analytics to join its data team in a fully remote capacity. The role centers on building scalable analytics infrastructure, data models, and ELT/ETL pipelines with dbt Core and SQL, plus API surfaces to power dashboards, ML features, and self-service analytics. Collaborating across product, analytics, and ML groups, you will translate business needs into robust data solutions.
Position overview
We are looking for an experienced Analytics Engineer to design and implement reliable, scalable analytics infrastructure that turns data into actionable insights. The focus is on crafting data models, transformation pipelines, and APIs that support dashboards, machine learning 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.
Responsibilities
- Design, develop, and maintain robust ELT/ETL data transformation pipelines using dbt Core and SQL targeting BigQuery.
- Create modular, tested SQL models and Python-based transformations to support analytics, reporting, and ML feature generation.
- Establish data quality checks, lineage, and observability to ensure reliable analytics outputs and meet 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 as appropriate.
- Optimize performance and cost for BigQuery workloads through partitioning, clustering, and query tuning.
- Document data models, transformation logic, and 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.
- Expert proficiency in SQL and strong Python skills for data transformation, orchestration, or testing.
- Experience working with Healthcare Claims Data.
- 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 incorporating 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.
- Nice to have: domain knowledge of healthcare claims and related data models.
- U.S. work authorization without visa sponsorship is required.
Technologies
- dbt Core
- SQL
- Python
- BigQuery
- Google Cloud Platform (GCP)
- Cloud Run
- Vertex AI
- FastAPI
- RESTful APIs
- LLM APIs
Location
Bristol, PA (remote); 100% remote
Position overview (summary)
We 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 focuses 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.
