> Markdown version of [/jobs/ext/2211343-data-engineer-nba](https://www.wearedevelopers.com/jobs/ext/2211343-data-engineer-nba). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - NBA - **Company:** Humana Inc. - **Location:** Boston, MA, United States (Remote available) - **Experience:** Expert - **Salary:** $117,600.0 - $161,700.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Artificial Intelligence, Data Architecture, Information Engineering, Data Governance, Programming Tools, Distributed Computing Environment, Internet Services, Python (Programming Language), Machine Learning, Operational Databases, Performance Tuning, Recommender Systems, Standard Sql, DataOps, Azure Data Lake, Data Streaming, Systems Integration, Reinforcement Learning, Feature Engineering, Data Ingestion, Azure Data Factory, GitHub Copilot, Apache Spark, Vue.js, Data Lakes, Data Lineage, Apache Kafka, Spark Streaming, Data Management, Data Pipelines, Workday, Databricks - **Published:** August 24, 2026 - **Apply:** https://www.dice.com/job-detail/2d8d6d82-f22f-47a6-a483-f24da12786ec ## About the Role 5+ years of data engineering experience building and operating production data platforms. Strong SQL and Python skills with hands-on experience developing Spark-based data pipelines. Experience with Databricks, Delta Lake, or comparable lakehouse platforms. Experience implementing Medallion Architecture (Bronze/Silver/Gold) data patterns. Experience building batch and streaming data processing pipelines. Strong understanding of data modeling, pipeline testing, data quality controls, and operational support practices. Familiarity with modern cloud-based data platforms and distributed data processing systems. Strong communication skills and the ability to collaborate across engineering, analytics, and business teams. Preferred Qualifications Experience with Databricks Feature Store, Unity Catalog, Delta Live Tables, and Databricks Workflows. Experience with Spark Structured Streaming and real-time feature engineering. Experience with Kafka and event-driven data architectures. Familiarity with machine learning, recommendation systems, reinforcement learning, or decision intelligence platforms. Experience with Azure Data Factory, Azure Data Lake Storage, Azure Event Hubs, or similar cloud-native data services. Experience with data observability and quality platforms such as Great Expectations, Monte Carlo, or equivalent tools. Experience integrating external healthcare, claims, CMS, CDC, consumer, or social determinants of health datasets. Background in healthcare, insurance, or another regulated industry with PHI/HIPAA handling requirements. We build with modern AI development tools (such as Claude and GitHub Copilot) and expect everyone on the team to use them to work faster and at higher quality. Work Style: Remote/Hybrid - Preferably Boston, MA. ## Description The Senior Data Engineer builds and evolves the data foundation that powers the NBA platform on the Databricks Lakehouse. This role is responsible for developing scalable data pipelines, feature engineering workflows, and real-time ingestion patterns that transform raw healthcare, member, behavioral, engagement, and socioeconomic data into trusted assets for decision intelligence, machine learning, reinforcement learning, and AI workloads. This is a hands-on engineering role focused on delivering reliable, well-governed, and high-quality data products while partnering closely with Data Science, AI Engineering, and Platform Engineering teams., Data pipeline development - Design, build, and maintain Bronze, Silver, and Gold lakehouse pipelines that power member profiles, clinical signals, engagement data, and decision intelligence use cases. Feature engineering - Develop and maintain Gold-layer feature tables and reusable data products that support model training, model scoring, reinforcement learning, and real-time decisioning. Batch and streaming ingestion - Build and support batch and real-time ingestion pipelines using Databricks, Spark, Delta Lake, and event-driven data architectures. Data quality engineering - Implement data quality validation, reconciliation, monitoring, alerting, and testing controls to ensure trusted and production-ready data assets. Data modeling - Design scalable data models that balance usability, governance, performance, and long-term maintainability. Performance optimization - Tune Spark workloads, storage strategies, partitioning schemes, and query performance to improve efficiency, scalability, and cost management. Data governance - Follow established standards for data lineage, security, PHI handling, auditability, and regulatory compliance. Platform integration - Partner with Decision Intelligence, AI Engineering, and Platform Engineering teams to ensure high-quality data is available across the NBA ecosystem. Operational support - Diagnose and resolve pipeline failures, data quality issues, and production incidents to maintain reliable platform operations., Occasional travel to Humana's offices for training or meetings may be required. Work Hours: Typical business hours are Monday-Friday, 8 hours/day, 5 days/week-- some flexibility might be possible, depending on business needs. Very minimal travel might be required for training, meetings, and/or conferences Interview Format As part of our hiring process, we will be using on-demand technology provided by Hire Vue, a third-party vendor. This technology provides our team of recruiters and hiring managers with an enhanced method for decision-making through on-demand candidate assessments. If you are selected to move forward from your application prescreen, you will receive correspondence inviting you to participate in an on-demand assessment with pre-determined questions. You should anticipate the assessment to take approximately 10-15 minutes. Your on-demand assessment will be reviewed, and you will subsequently be informed if you will be moving forward to next round of interviews. SSN Task via Workday Should you be extended a formal employment offer you will receive a request to enter your SSN into our Workday system to scan for duplicate profiles. Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information. Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. 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