SENIOR DATA ENGINEER
Talent Software Services
Senior Data Engineer
Design and operate production ETL/ELT pipelines on enterprise cloud platforms (GCP and Azure) for healthcare data. The role owns pipelines end-to-end — from requirements through deployment and ongoing operations — and is expected to set technical direction when requirements are unclear, not wait for it.
Core Responsibilities:
- Design, build, and operate scalable ETL/ELT pipelines across GCP, Azure, BigQuery, and SQL Server.
- Model data for analytical workloads — dimensional modeling, SCDs, and schema design.
- Orchestrate pipelines using Airflow, Cloud Composer, Azure Data Factory, or similar.
- Handle PHI in line with HIPAA requirements — secure movement, de-identification, access controls, and audit.
- Deploy via Git and CI/CD; monitor and maintain pipelines in production.
- Translate stakeholder needs into technical plans; communicate feasibility and tradeoffs early.
- 7+ years in data engineering, with significant time at senior level delivering production systems.
- Strong SQL plus Java or Python for pipeline development.
- Hands-on across multiple cloud stacks (e.g., GCP, Azure, BigQuery, SQL Server).
- Deep experience designing and operating reliable, scalable ETL/ELT pipelines; performance-minded.
- Hands-on with at least one orchestration tool (Airflow, Cloud Composer, ADF, Dagster, or Prefect).
- Strong data modeling skills — dimensional modeling, normalization, slowly-changing dimensions.
- Working knowledge of HIPAA and PHI handling — secure movement, de-identification, access controls, audit.
- Track record delivering on enterprise cloud platforms within standards and controls.
- Proficient with Git and CI/CD.
- End-to-end ownership: Drives delivery from definition through production with minimal direction; prioritizes operational delivery, not just prototypes.
- Business translation: Converts stakeholder needs into clear technical plans; communicates feasibility and value early.
- Proactive exploration: Evaluates new tools, runs lightweight proofs of concept, and shares findings.
- Industry awareness: Tracks modern data trends (semantic layers, LLM-assisted dev, modern ELT) and brings relevant insights back.
- Continuous learning: Adapts quickly while maintaining consistent delivery.
Technical Requirements:
Other Requirements:
Vacancy posted 4 days ago
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