Everforth CyberCoders is seeking a Senior Data Engineer in Analytics to join a Bristol, PA based team with remote work options. The role centers on designing and implementing data models, ELT/ETL pipelines, and APIs that power dashboards, ML features, and downstream systems, collaborating with data scientists, analysts, and engineers to standardize metrics and elevate data quality. This position emphasizes enabling self-service analytics across the organization while meeting performance and reliability expectations.
Position overview
We are looking for an experienced Analytics Engineer to help build reliable, scalable analytics infrastructure that converts raw data into actionable insights. The focus is on crafting data models, transformation pipelines, and APIs that support dashboards, machine learning features, and downstream applications. You will partner with product, analytics, and ML teams to codify metric definitions and deliver high-quality data products across the enterprise.
Responsibilities
- Architect and maintain end-to-end ELT/ETL pipelines using dbt Core and SQL with BigQuery as the target.
- Develop modular, tested SQL models and Python-based transformations to support analytics, reporting, and ML feature generation.
- Implement data quality checks, lineage, and observability to ensure reliable analytics outputs and adherence to 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; incorporate LLM APIs where applicable.
- Deploy and monitor data services and lightweight API endpoints on GCP, leveraging Cloud Run and other serverless options when suitable.
- Optimize BigQuery performance and cost management through partitioning, clustering, and query tuning.
- Document data models, transformation logic, and operational runbooks; mentor teammates on dbt, SQL, and analytics engineering best practices.
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 experience 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 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.
- Must be authorized to work in the United States without the need for visa sponsorship.
Technologies
- dbt Core
- SQL
- Python
- BigQuery
- Google Cloud Platform (GCP)
- Cloud Run
- RESTful APIs
- LLM APIs
- Vertex AI
- FastAPI
Location
Bristol, PA (remote) with 100% remote work option.
Additional details
This role emphasizes collaboration across product, analytics, and ML teams, with a focus on standardizing metrics, improving data quality, and enabling self-service analytics through robust data models, pipelines, and APIs.
