Senior Data Engineer

Senior Data Engineer

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The Senior Data Engineer designs, builds, and maintains data processing solutions that enable the efficient transformation of structured and unstructured data into meaningful insights. Working closely with engineers and cross‑functional partners, this role contributes to data ingestion from internal and external sources using cloud‑native platforms, established engineering best practices, and proven design patterns.

This position supports the design, development, and maintenance of scalable data solutions and supporting software applications based on business requirements. The work involves moderately complex to complex problem solving and requires in‑depth analysis of data, systems, and variable factors. The Data Engineer ensures reliable collection, storage, processing, and analysis of large data sets while aligning solutions with enterprise architecture standards.

Exceptional outcomes begin with exceptional talent. They begin with you.

• Design, develop, and maintain scalable data pipelines and workflows using Azure Databricks.
• Develop and maintain SAS programs and SSIS packages for intermediate and downstream data processing.
• Write, optimize, and maintain complex SQL queries to support data transformation and analytical use cases.
• Design and build ETL/ELT pipelines integrating data from multiple internal and external source systems.
• Select, implement, and support Big Data tools and frameworks for data processing and integration.
• Monitor, troubleshoot, and resolve complex data processing issues, applying root cause analysis and preventative fixes.
• Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
• Recommend and support infrastructure improvements to meet evolving data volume and processing demands.
• Partner with product management and SRE teams to define requirements and translate them into actionable engineering work.
• Collaborate effectively with engineers, stakeholders, and cross‑functional teams to ensure alignment on data strategy, architecture, and outcomes.

• Bachelor’s degree in a science, engineering, or computing related discipline or equivalent practical experience.
• 8+ years of experience designing and building production‑grade batch data pipelines for data ingestion and transformation.
• 8+ years of overall experience in data engineering or related roles.
• Strong proficiency in SQL, Databricks, Python, Apache Spark, Git, Azure Services (Synapse, Azure ADLS Gen
  2).
• Strong understanding of relational database principles, data modeling, database management, and data warehousing.
• Strong knowledge of Big Data querying tools.
• Experience optimizing large‑scale data pipelines and ETL workflows.
• Excellent communication and interpersonal skills.

• Experience with cloud migrations and legacy modernization.
• Experience with Snowflake.
• Experience in the healthcare space designing systems to protect member PHI and PII.

• Remote position with occasional travel to Humana offices for training or meetings.
• Work‑at‑home requirement: home internet download speed of 25 Mbps and upload speed of 10 Mbps recommended; wired or wireless approved.
• Internet stipend for eligible employees in California, Illinois, Montana, or South Dakota.
• Compensation range: $117,600 – $161,700 per year (subject to geographic location and qualifications).
• Eligible for bonus incentive plan.
• Paid time off, vacation, holiday, volunteer time off, paid parental and caregiver leave, 401(k) retirement plan with company match.
• Health, dental, vision, short‑term & long‑term disability, life insurance.
• Well‑being program and resources.

Work hours:

40 hours per week.

Humana is an equal opportunity employer. It does not discriminate on the basis of race, color, religious, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability, or protected veteran status. Humana complies with all applicable federal civil rights laws and also provides free language interpreter services.