Design, build, and maintain scalable data pipelines and architectures to support analytics, machine learning, and operational applications.
Collaborate with cross-functional teams to translate complex operational needs into reliable, well-modeled datasets.
Integrate and normalize data from multiple structured and unstructured healthcare sources (EHRs, scheduling systems, operational databases, etc.).
Optimize query performance and data processing for speed, scalability, and cost efficiency.
Implement best practices for data quality, governance, and security in compliance with healthcare regulations (e.g., HIPAA).
Support deployment, monitoring, and troubleshooting of production data systems.

Proven experience as a data engineer or in a similar role, with a track record of building and maintaining large-scale data infrastructure.
Strong proficiency in SQL and Python for data processing and pipeline development.
Experience with cloud data platforms and services such as AWS (RDS, Redshift, Lambda, S3), GCP, or Azure.
Knowledge of both relational and non-relational databases (PostgreSQL, MySQL, MongoDB, etc.).
Familiarity with modern data workflow orchestration tools (Airflow, DBT, Dagster, etc.).
Ability to work closely with both technical and non-technical stakeholders to gather requirements and deliver solutions.
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.

Forward Deployed Data Engineer

Key skills