Data Engineer, Consultant

Releady is partnering with a leading healthcare technology company to hire a Data Engineer, Consultant 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 is a senior individual contributor and technical leader who reports to a Senior Manager or Manager within Data Solutions and drives end-to-end delivery of complex data engineering solutions across cloud data platforms. The Consultant partners closely with Solution Design Leads, Architects, Product Managers, and business stakeholders to translate solution designs and business requirements into scalable, secure, production-ready data products, and provides technical leadership and mentorship without formal people management responsibility.

NOTE:  *Must be eligible to work on W2 without sponsorship. Not eligible for C2C.

• Pay Rate: $70–$80/hr
• Duration: 6-month contract-to-hire
• Location: Hybrid or Remote, however must reside in the following states: WA, OH, CA, AZ, CO, CT, FL, GA, MD, MN, NV, OR, AL, IL, VA, WI, TX, NY

 

Solution Architecture & Delivery

●        Lead the design and implementation of complex data pipelines and data products from development through production.

●        Translate solution designs and business requirements into detailed technical architecture and implementation plans.

●        Architect and build scalable, secure, and highly available data solutions across enterprise data platforms.

●        Apply advanced data modeling techniques, including Data Vault 2.0, dimensional, and domain-oriented models, to support analytics and reporting needs.

Quality, Security & Operational Excellence

●        Embed data quality, testing, security, and observability by design across data pipelines.

●        Drive operational excellence, including incident analysis, stabilization, performance tuning, and deployment optimization.

●        Identify and implement optimization opportunities related to performance, reliability, and cloud cost management.

Technical Leadership & Standards

●        Influence and evolve the data engineering standards, patterns, and frameworks used by delivery teams.

●        Provide technical leadership and mentorship to Data Engineers and Senior Data Engineers through design reviews and code reviews.

●        Work within an agile / DevSecOps pod model, collaborating closely with solution leads, data modelers, analysts, and business partners.

AI Enablement & Stakeholder Communication

●        Support integration of AI/ML-ready datasets by ensuring data is well-modeled, reliable, and governed.

●        Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

 

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

●        Advanced hands-on expertise in SQL, including automation and pipeline optimization.

●        Strong experience with cloud platforms, Azure preferred, and services such as ADLS, Synapse, and Data Factory.

●        Extensive experience with modern data platforms including Snowflake and Databricks, and orchestration tools such as Airflow or Tidal.

●        Deep understanding of data modeling, integration patterns, data architecture, data quality, and data warehousing.

●        Proven experience implementing CI/CD pipelines, Infrastructure as Code, and DataOps practices.

●        Strong understanding of security, privacy, and compliance requirements in regulated environments.

●        Experience working with large-scale, distributed data platforms and parallel processing architecture.

●        Excellent communication and stakeholder engagement skills, with a proven ability to lead technically without formal people management responsibility.

●        Healthcare industry experience is preferred, including exposure to Epic or similar ecosystems.