Senior Healthcare Data Engineer – AWS & Python

Our client is a leader in healthcare analytics and technology, focusing on transforming healthcare through data innovation.

• At least 6 years of professional experience in data engineering, preferably in healthcare or related industries.
• Strong proficiency in Python (3.12+) with modern data libraries.
• Hands-on experience with AWS data infrastructure including S3, Athena, IAM, and Glue.
• Advanced SQL skills capable of handling large datasets with complex queries, window functions, and cohort analysis.
• Proven ability to develop and optimize production-grade data pipelines processing billions of rows.
• Familiarity with Git workflows, code reviews, and documentation practices.
• Experience merging disparate healthcare data sources and managing high data quality.

Nice to have:

• Healthcare industry experience including claims, patient journey analysis, ICD/CPT coding, PHI/HIPAA compliance.
• Experience with multi-cloud platforms, especially Azure.
• Knowledge of healthcare provider databases, NPI, and patient journey analytics.
• Skills in advanced data modeling, data cataloging, and metadata management.
• Exposure to AI/LLM data systems, prompt engineering, and structured outputs (JSON/YAML).
• Experience with orchestration tools such as Airflow, Dagster, or Step Functions.
• Familiarity with PostgreSQL, Supabase, and dashboards.

• Design and build production ETL/ELT pipelines from diverse healthcare data sources into AWS S3 data lakes and warehouses.
• Implement batch workflows with orchestration, error handling, retries, and lineage tracking.
• Develop Python-based data processing jobs using modern libraries to merge, transform, and normalize healthcare datasets.
• Optimize AWS data stack components including S3, Athena, IAM, and Glue for cost efficiency and performance.
• Manage large healthcare datasets such as claims, patient records, referrals, and clinical information ensuring data quality and integrity.
• Write and optimize complex SQL queries for analytical and cohort analysis, hospital performance metrics, and patient segmentation.
• Maintain data quality through validation, anomaly detection, schema enforcement, and automated validation pipelines.
• Monitor and enhance pipeline throughput, memory efficiency, and cloud query cost management.

Only candidates with an existing legal right to work in the European Union will be considered for this role.