Data Engineer, Principal

United States Digital Space LLC

United States

Hybrid

USD 117,096 - 130,872

Full time

14 days+

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Job summary

United States Digital Space LLC is seeking a Principal Data Engineer to lead the Data Services team in designing scalable data pipelines, data lakes, data warehouses, and data marts for enterprise health data.

You will mentor engineers, influence architecture decisions, and apply Data Vault 2.0, lakehouse concepts, and AI-ready data assets across Snowflake, Databricks, and Synapse.

Qualifications

  • Bachelor's degree or equivalent experience with 10+ years in data engineering.
  • Experience supporting enterprise AI/ML and data products.
  • Expertise in Data Vault 2.0, dimensional modeling, and Lakehouse architecture.
  • Influence on enterprise architecture and mentorship of senior engineers.
  • Strong data management, modeling, and security practices.
  • Hands-on with SQL, Python, DBT Cloud/Core; fluency in Snowflake, Synapse, Databricks.
  • Ability to design and scale large data platforms with parallel/distributed architectures.
  • CI/CD, source control, and agile tooling (Git, Bitbucket, Jira).
  • Healthcare/regulated enterprise experience preferred.

Responsibilities

  • Lead design and delivery of scalable data pipelines for data lakes, warehouses, and marts.
  • Engineer ELT/ETL processing of structured and semi-structured data.
  • Apply Data Vault 2.0 and dimensional modeling for analytics.
  • Collaborate with Architecture, Product, and Solution teams to implement designs.
  • Build on Snowflake, Databricks, Synapse with performance, cost, and reliability focus.
  • Embed data quality, governance, and observability into pipelines; apply DataOps best practices.
  • Provide hands-on leadership and mentor senior engineers; promote engineering standards.
  • Support AI/ML data readiness and enterprise analytics initiatives.

Skills

SQL
Python
DBT Cloud
DBT Core
NoSQL
Snowflake
Synapse
Databricks
Data Vault 2.0
Dimensional modeling
Lakehouse architecture
Domain-driven design
CI/CD
Git
Bitbucket
Jira

Education

Bachelor's degree or equivalent experience

Tools

DBT Cloud
DBT Core
Snowflake
Synapse
Databricks
Git
Bitbucket
Jira

Job description

OVERVIEWthe company 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.*

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