Principal Data Engineer

Humana • Boston, MA

4d • Hybrid

About The Position

The Principal Data Engineer owns the design and delivery of the NBA platform's data pipelines on the Databricks Lakehouse. This is a hands-on engineering role first - you are expected to be a significant individual contributor building production pipelines every sprint. You also lead a small team of data engineers and contractors, and are accountable for the quality, reliability, and timeliness of the data that feeds the platform's AI models and decisioning system.

Requirements

• Bachelor's degree in computer science or relevant field
• 10+ years of data engineering experience with at least 1-2 years in a tech lead or senior lead capacity
• Deep hands-on experience with Databricks and Delta Lake - you have built and owned production pipelines, not just contributed to them
• Strong SQL and Python skills; comfortable with Spark at scale
• Experience designing and owning a medallion lakehouse architecture (Bronze/Silver/Gold or equivalent)
• Proven ability to lead a small team or pod through delivery and manage contractor resources
• Strong data quality instincts - you treat bad data as a production incident
• Clear communicator - you can explain a pipeline design decision to a data scientist, a product owner, and a compliance officer
• Comfort using AI productivity tools (Claude, Copilot, or similar) to accelerate development and analysis

Nice To Haves

• Masters degree
• Experience with Databricks Delta Live Tables, Unity Catalog, and Feature Store
• Familiarity with Kafka-based event pipelines and real-time data ingestion
• Background in healthcare, insurance, or other regulated industries with PHI/HIPAA data handling requirements
• Experience integrating government or third-party datasets (CMS, CDC, STARS, or similar)

Responsibilities

• Pipeline delivery - design, build, and own the Bronze/Silver/Gold lakehouse pipelines that power the NBA platform: member profiles, clinical signals, behavioral data, web clickstream, and socioeconomic features
• Hands-on development - actively write and ship production SQL, Python, and Spark code alongside your team; this is not a supervisory role
• Data modeling - own the Gold layer schema that serves as the canonical member feature set for model training and batch scoring; make design decisions that balance flexibility, performance, and governance
• Data quality - build and maintain data quality checks, null/sparsity monitoring, and pipeline alerting so the team knows before anyone else when something is wrong
• External data integration - onboard new data sources (clinical feeds, government datasets, third-party signals) from raw ingestion through production-ready features
• Contractor management - manage data engineering contractors within your pod; set expectations, review work, and hold the team to quality standards
• Cross-functional partnership - work closely with the Principal Decision Intelligence Engineer on feature requirements, and with software engineering pods on how data flows into the decisioning system

Benefits

• medical
• dental
• vision benefits
• 401(k) retirement savings plan
• time off (including paid time off, company and personal holidays, paid parental and caregiver leave)
• short-term and long-term disability
• life insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Principal