Principal Data Engineer

Overview

Principal Data Engineer – Own the design and delivery of the NBA platform's data pipelines on the Databricks Lakehouse. This is a hands‑on engineering role where 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 you are accountable for the quality, reliability, and timeliness of the data that feeds the platform’s AI models and decisioning system.

• 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

• Sponsorship is not available for this role
• 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

• Master’s 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)

Remote/Hybrid – Preferably Boston, MA. Occasional travel to Humana’s offices for training or meetings may be required. Typical business hours are Monday‑Friday, 8 hours/day, 5 days/week with some flexibility depending on business needs.

Work‑From‑Home requirements:
Must have a high‑speed DSL or cable modem (minimum 25 Mbps download × 10 Mbps upload) and a dedicated space free of interruptions to protect member PHI/HIPAA information. Satellite and wireless Internet service are not allowed. Associates or contractors living in California will receive reimbursement for Internet expenses.

Humana is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability, or protected veteran status. We take affirmative action in compliance with Section 503 of the Rehabilitation Act and VEVRAA.