Data Engineer, Principal

Releady; Denver (CO); Hybrid; USD 117,096 - 130,872; Full time

Job summary

Releady, partnering with a leading healthcare technology company, seeks a Principal Data Engineer to design scalable data pipelines, data lakes, warehouses, and data marts across enterprise platforms. Lead delivery, mentor engineers, and influence architecture while collaborating with Enterprise Architects and Data Engineering teams.

The role supports AI-enabled analytics, data quality and governance, and DevOps/DataOps practices.

Qualifications

• Bachelor's degree or equivalent with at least ten years in data engineering.
• Experience supporting enterprise AI/ML, analytics, and data products.
• Expertise in Data Vault 2.0, dimensional modeling, lakehouse architecture, or domain-driven data design.
• Ability to influence enterprise architecture decisions and mentor senior engineers.
• Strong data management skills including data modeling, MDM, integration, privacy, and security.
• Hands-on with SQL, Python, DBT Cloud, DBT Core; fluent with Snowflake, Synapse, or Databricks.
• Experience designing large-scale, high-performance data platforms.
• Knowledge of CI/CD, source control, and agile tools (Git, Bitbucket, Jira).
• Healthcare or regulated environments experience preferred.

Responsibilities

• Lead design, development, and implementation of scalable data pipelines for data lakes, warehouses, and marts.
• Engineer ELT/ETL to ingest and curate structured and semi-structured data from diverse sources.
• Apply Data Vault 2.0, dimensional, and domain-driven modeling for analytics products.
• Partner with Solution Design, Architecture, and Product teams to ensure secure designs.
• Build on Snowflake, Databricks, and Synapse with performance, scalability, and cost efficiency.
• Implement data quality, observability, lineage, and governance in pipelines.
• Champion CI/CD, automated testing, IaC, monitoring, and alerting in DataOps.
• Provide hands-on leadership and mentorship to data engineers; promote best practices.
• Support AI/ML-ready data assets and ensure trustworthy data for advanced analytics.

Skills

Data modeling

Data Vault 2.0

AI/ML readiness

Enterprise architecture

Mentoring

SQL

Python

NoSQL

CI/CD

Agile

Education

Bachelor's degree or equivalent

Tools

Snowflake

Databricks

Synapse

DBT Cloud

DBT Core

Git

Bitbucket

Jira

Job description

OVERVIEW

Releady is partnering with a leading healthcare technology company to hire a Data Engineer, Principal 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 reports to a Senior Manager, Data Solutions, or Director, and partners with Enterprise Architects, Portfolio, Analytics, and Data Engineering teams to design technical solutions and build data products that meet enterprise-wide data needs. The Principal drives data product delivery by designing and implementing cloud data lakes, data warehouse, and data mart solutions, and is expected to influence enterprise architecture decisions and mentor senior engineering talent.

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

• Pay Rate: $85–$95/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

RESPONSIBILITIES

Data Platform Architecture & Delivery

• Lead the design, development, and implementation of scalable data pipelines supporting enterprise data lakes, data warehouses, and data marts.
• Engineer robust ELT/ETL solutions that ingest, process, and curate structured and semi-structured data from diverse internal and external sources.
• Apply advanced data modeling techniques, including Data Vault 2.0, dimensional, and domain-oriented models, to support analytics and data products.

Cross-Functional Solution Design

• Partner with Solution Design, Architecture, and Product teams to ensure technical designs are implemented accurately, efficiently, and securely.
• Build and optimize data solutions on cloud platforms such as Snowflake, Databricks, and Synapse, with a focus on performance, scalability, reliability, and cost efficiency.

Quality, Governance & Operations

• Implement data quality, validation, observability, lineage, and governance controls embedded directly into data pipelines.
• Champion and apply DevOps and DataOps best practices, including CI/CD, automated testing, infrastructure as code, monitoring, and alerting.
• Identify performance bottlenecks, reliability risks, and optimization opportunities across data platforms and workflows.

Technical Leadership & AI Enablement

• Provide hands‑on technical leadership and mentorship to senior and mid‑level data engineers, promoting engineering standards and best practices.
• Collaborate using agile methodologies to plan work, refine technical stories, and deliver iteratively with predictable outcomes.
• Support integration of AI/ML‑ready data assets, ensuring data is trustworthy, well‑modeled, and accessible for advanced analytics use cases.
• Act as a technical thought leader, advocating for modern data engineering patterns, tools, and practices aligned to enterprise strategy.

QUALIFICATIONS

• Bachelor's degree or equivalent experience, with a minimum of ten years of relevant data engineering experience.
• Experience supporting enterprise AI/ML, advanced analytics, and data product ecosystems.
• Expertise in Data Vault 2.0, dimensional modeling, Lakehouse architecture, or domain-driven data design.
• Demonstrated ability to influence enterprise architecture decisions and mentor senior engineering talent.
• Expert‑level understanding of data management practices, including data modeling (Data Vault 2.0), master data management, data integration, architecture, virtualization, warehousing, privacy, and security.
• Demonstrated enthusiasm for AI and emerging technologies, with hands‑on experience applying AI‑driven solutions in enterprise environments.
• Hands‑on experience with SQL, Python, DBT Cloud, and DBT Core; expert‑level fluency in NoSQL and database platforms such as Snowflake, Synapse, or Databricks.
• Proven ability to design and scale large‑volume, high‑performance data platforms leveraging parallel and distributed architectures.
• Advanced knowledge of CI/CD, source control, and agile delivery tooling such as Git, Bitbucket, and Jira.
• Experience in healthcare, regulated environments, or large enterprises is strongly preferred.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non‑merit factor. We are committed to creating a diverse and inclusive environment for all employees.