Data Engineer

Role Overview

Aretum is seeking a Data Engineer to build and manage end-to-end data pipelines, including ingestion, transformation, reconciliation, and analytics. The work may involve handling Controlled Unclassified Information (CUI) and requires adherence to federal safeguarding and compliance requirements.

Responsibilities

• Ingest data from FHIR APIs, CDW, and other VA sources
• Normalize and reconcile medication and patient data
• Build transformation pipelines supporting risk scoring inputs
• Support batch and near-real-time processing
• Ensure data quality, consistency, and traceability

Requirements

• Python (primary), SQL (advanced); optional Scala
• Data processing frameworks: Apache Spark, AWS EMR, Databricks (preferred)
• ETL/ELT design: pipeline orchestration, incremental vs full loads, data validation
• API integration: REST APIs, JSON parsing, pagination, OAuth2 authentication
• FHIR data handling (e.g., Patient, MedicationRequest, Observation)
• Data modeling: relational and semi-structured schema design
• Data quality & validation: deduplication, reconciliation logic, anomaly detection
• Streaming vs batch processing tradeoffs and implementation patterns
• Storage: S3, relational databases, basic NoSQL knowledge
• Performance optimization: partitioning, parallelization, query tuning
• Versioning & lineage: data version control, reproducibility of datasets

Nice-to-Haves / Preferred

• Databricks experience

Travel / Work Location

• Remote position with occasional travel (<10%) for project needs, client meetings, collaboration, or training.

Security / Eligibility

• Public Trust eligibility required
• Ability to obtain and maintain a Public Trust or Suitability Determination (based on agency requirements)
• U.S. citizenship required due to federal contract requirements