Data Engineer, Senior (Hybrid)

Releady

San Francisco, UShybrid$60k-$70k/yrPosted Jul 21, 2026
Posting intelligenceActively listed

Skills

databrickssnowflakeairflowgithubazureepiccicddbt

About the role

OVERVIEW

Releady is partnering with a leading healthcare technology company to hire a Data Engineer, Senior for its Data Services team. This organization provides the technology backbone and shared data infrastructure for nonprofit, community, and regional health plans nationwide, unifying clinical, claims, demographic, and provider data into a single governed platform that powers automation and AI deployment across core health plan operations.

This role will report to a Senior Manager or Manager within Data Solutions and will independently design, build, and operate complex data pipelines and cloud data solutions, embedding security, automation, and reliability throughout the software development lifecycle. The Data Engineer, Senior is a hands-on technical leader who ensures production readiness and operational excellence across the organization's data products, and who mentors other engineers while contributing to engineering best practices.

NOTE: Must be able to work in the United States without sponsorship

Employment Type: Contract-to-Hire (six-month contract term)

Location: Hybrid - 2x/week onsite; San Diego, Long Beach, Sacramento, Rancho Cordova, or Oakland (SF Bay Area)

Compensation: $60 – $70/hr

RESPONSIBILITIES

Data Pipeline Design & Delivery

Design, build, and maintain complex data pipelines from development through production for multiple use cases.

Develop efficient, scalable, and cost-effective implementations by leveraging reusable frameworks and patterns.

DevSecOps & Quality Integration

Integrate security, automation, and quality controls throughout the software development lifecycle using DevSecOps best practices.

Implement and maintain automated testing, validation, and monitoring frameworks for data workflows.

Leverage AI-assisted approaches across development, testing, and deployment to reduce operational overhead and improve quality.

Operational Excellence

Drive incident management, root cause analysis, and deployment stability.

Monitor and manage software configuration changes to proactively address data reliability and customer experience issues.

Coordinate sustaining support for multiple data platforms or business processes within a cloud environment.

Perform monitoring, tuning, and optimization of data pipelines to ensure performance, availability, and efficient resource utilization.

Cross-Functional Collaboration & Leadership

Work within an agile / DevSecOps pod model alongside solution leads, data modelers, analysts, and business partners.

Translate complex functional requirements into robust technical designs.

Mentor and support Data Engineers through code reviews, knowledge sharing, and engineering guidance.

Apply domain knowledge of healthcare and enterprise IT trends to inform solution delivery.

QUALIFICATIONS

Bachelor's degree or equivalent experience, with a minimum of five years of relevant data engineering experience.

Strong hands-on experience with SQL, including scripting and automation.

Expertise with cloud platforms, Azure preferred, and services such as ADLS, Synapse, and Data Factory.

Hands-on experience with modern data stack tools such as dbt, Snowflake, Databricks, Airflow, or Tidal.

Solid knowledge of data modeling using Data Vault 2.0, along with data integration, data architecture, warehousing, and data quality.

Experience implementing CI/CD pipelines using tools such as Bitbucket or GitHub.

Strong understanding of agile delivery methodologies and enterprise cloud integration.

Excellent communication skills, with the ability to translate technical solutions for non-technical stakeholders.

Experience in healthcare or other regulated environments is preferred; Epic ecosystem exposure is a plus.

Awareness of data governance, security standards, and production certification processes.

Compensation

This Data Engineer role pays $60k-$70k/yr. Within typical range for data engineer roles in United States.

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