Senior Data Engineer

Humana

3d•$117,600 - $161,700•Remote

About The Position

The Senior Data Engineer designs, builds, maintains, and optimizes scalable data pipelines and data-driven solutions. The role enables efficient ingestion, storage, processing, and analysis of structured and unstructured data from internal and external sources, while ensuring data quality, reliability, performance, scalability, and cost efficiency. The position applies cloud-native platforms, established engineering best practices, and proven design patterns to meet business and analytical needs and align solutions with enterprise architecture standards. The role involves developing and maintaining Azure Databricks pipelines, SAS programs, SSIS packages, and complex SQL transformations. The Senior Data Engineer evaluates and selects appropriate technologies, monitors workflows, troubleshoots complex processing issues, and improves data platform capabilities. The position also contributes to solutions that use big data, artificial intelligence, and machine learning to transform data into actionable insights. The Senior Data Engineer works closely with software engineering, analytics, product management, SRE teams, stakeholders, and other cross-functional partners. The role is suited to a collaborative person who can work in a fast-paced, iterative environment and solve complex problems. This is a remote position; occasional travel to Humana offices for training or meetings may be required.

Requirements

Bachelor’s degree in a science, engineering, or computing-related discipline, or equivalent practical experience.
At least 8 years of experience designing and building production-grade batch data pipelines for data ingestion and transformation.
At least 8 years of overall experience in data engineering or related roles.
Strong proficiency in SQL, Databricks, Python, Apache Spark, Git, and Azure services including Synapse and 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.

Nice To Haves

Experience working on cloud migrations and legacy modernization.
Experience working with Snowflake.
Experience in healthcare and designing systems to protect member PHI and PII.

Responsibilities

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 for 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 using root cause analysis and preventative fixes.
Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
Recommend and support infrastructure improvements to meet changing data volume and processing demands.
Partner with product management and SRE teams to define requirements and translate them into actionable engineering work.
Collaborate with engineers, stakeholders, and cross-functional teams to align on data strategy, architecture, and outcomes.
Contribute to data and software solutions using big data, artificial intelligence, and machine learning techniques.