Senior Data Engineer

Humana

Closes in 6 days Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $117,600–$161,700 / yr
Posted: 3 days ago
Closes: Jun 26, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $171k

This role $140k

$106k most similar roles pay here $226k

This role pays less than 73% of similar roles. Most pay $137,450–$205,000 — the shaded band above. At the midpoint, this role pays about $140k versus about $171k for comparable roles.

Based on 240 similar postings.

Employer

About Humana

Humana Inc. is a leading American for-profit health insurance company based in Louisville, Kentucky, specializing in Medicare Advantage plans.

Humana currently has 23 open roles on FindRole.

Listed pay typically runs $142,300–$195,700 across 23 roles with salary data.

Most-posted roles

View all roles at Humana

At a glance

TL;DR · Senior Data Engineer

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The Senior Data Engineer at Humana will join the data engineering team to design and maintain scalable data processing architectures that convert structured and unstructured data into actionable insights for enterprise-wide use. This role involves ingesting data from various sources using cloud-native platforms like Databricks, developing tools with AI and machine learning techniques, and optimizing existing applications and pipelines. The Senior Data Engineer will collaborate closely with business users and cross-functional teams to ensure system designs align with requirements and architecture standards while also contributing to the modernization of legacy on-premise SQL environments to cloud-based solutions. Key skills include experience in data integration, system modernization, Databricks, PySpark, SparkSQL, Unity Catalog, Delta Lake, and Azure Cloud.

Skills

Databricks PySpark SparkSQL Delta Lake Azure Cloud SQL CI/CD Kafka Hadoop AWS PostgreSQL Oracle Python Java Git Jenkins Terraform Kubernetes

What you'll do

Analyze business requirements to design system-level solutions for reporting and analytics.
Identify inefficiencies in data pipelines and recommend improvements for better performance.
Design and support workflows for data ingestion from internal and external sources.
Implement modernization of data platforms, integrating legacy systems with cloud-based tools.
Develop approaches for reliable and secure data migration across enterprise systems.
Coordinate with cross-functional teams to ensure technical tasks meet delivery timelines.

What we're looking for

Minimum 5 years experience in enterprise data platform support and modernization.
Strong background in cloud-based data engineering using Databricks, SQL, PySpark, SparkSQL.
Expertise in designing and implementing data ingestion and integration workflows.
Experience with system-level solutions for reporting, analytics, and data-driven processes.
Proficient in evaluating and recommending technologies for data platform optimization.

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