Data Engineer

Century Health is a clinical data intelligence company turning messy real-world clinical data into structured, analysis-ready insights for researchers and pharma teams.

The Role

We're looking for a ** Data Engineer (3–5 years)** to be a core builder on our data platform — designing ETL pipelines, profiling raw clinical datasets, and ensuring data flowing through our systems is clean and reliable.

What You'll Do

• Design, build, and maintain ETL/ELT pipelines ingesting data from CSVs, Parquet, XLSX, APIs, and databases
• Optimize pipeline performance — tune queries, manage compute, reduce latency and cost
• Profile raw datasets to identify quality issues: missing values, duplicates, schema drift, outliers
• Build and maintain dbt models for clean, documented, analysis-ready data layers
• Orchestrate workflows using Apache Airflow on AWS MWAA
• Process large-scale data using PySpark on EMR
• Collaborate with ML engineers and GTM teams on downstream use cases
• Document pipelines, models, assumptions, and known issues clearly

What We're Looking For

Must-Have

• 3–5 years of professional data engineering experience
• Strong SQL — window functions, CTEs, query optimization
• Solid Python — clean, modular, production-grade code
• Hands-on PySpark for large-scale processing
• Experience with dbt, Snowflake, and cloud-based ETL/ELT
• Familiarity with AWS: S3, MWAA, ECS Fargate, EMR, RDS, Bedrock
• Strong data intuition and ability to work independently in ambiguous environments
• Experience with test suites — pytest, Great Expectations, dbt tests
• Active use of AI coding tools (Cursor, Claude Code, etc.)
• Immediate Joiners only (1 month notice period). We can be flexible for exceptional candidates.

Nice to Have

• Healthcare data experience (HIPAA, FHIR, HL7, OMOP)
• Data science background (statistical modeling, ML pipelines, feature engineering)
• DevOps exposure (CI/CD, Docker, Terraform/CDK)

Tech Stack

• Cloud: AWS (MWAA, ECS Fargate, EMR, RDS, S3, Bedrock)
• Data Warehouse: Snowflake
• Transformation: dbt
• Processing: PySpark, Python
• Orchestration: Apache Airflow (MWAA)
• AI Tools: Cursor, Claude Code

Hiring Process

1. Application Review
2. Take-Home Assignment (~3 hours, real clinical data)
3. Technical Interview
4. Managerial Interview

Why Century Health

• Hard data problems with real clinical impact
• Small, high-ownership team — your work ships and matters
• Modern cloud-native stack with architectural influence
• AI-first engineering culture