Data Engineer, Principal

Blue Shield of CA; Kansas City (MO); On-site; USD 150,000 - 210,000; Full time

Job summary

Blue Shield of CA in the United States is seeking a Principal Data Engineer to lead end‑to‑end data product design. You will architect cloud data lakes, data warehouses, and data marts while partnering with Enterprise Architects, analytics, and data teams to meet enterprise needs.

The role emphasizes leadership, critical thinking, and delivering high‑performing data platforms. With a strong background in Data Vault 2.0, dimensional modeling, and Lakehouse architectures, you will mentor senior

Qualifications

• Requires a bachelor's degree or equivalent experience.
• Requires a minimum of 10 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 in understanding data management practices, data modelling (data vault 2.0), master data management, data integration, data architecture, data virtualization, data warehousing, data privacy and security.
• Demonstrated enthusiasm for AI and emerging technologies, with solid understanding of AI/ML concepts and hands‑on experience applying AI‑driven solutions in enterprise environments.
• Hands on experience with SQL, Python, DBT Cloud and DBT core. Expert in one or more of NoSQL and database appliances and platforms (Snowflake, Synapse, 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 (e.g., Git, Bitbucket, Jira).
• Experience in healthcare, regulated environments, or large enterprises is strongly preferred.

Responsibilities

• Design and deliver cloud-based data lakes, data warehouses, and data marts as enterprise data products.
• Partner with Enterprise Architects and data teams to shape technical solutions for data needs.
• Mentor senior engineers and influence architecture decisions across programs.
• Drive CI/CD, version control, and agile tooling to ensure scalable, reliable data platforms.
• Lead data engineering initiatives in healthcare or regulated enterprise contexts.

Skills

Data Vault 2.0

Dimensional modeling

Lakehouse architecture

AI/ML concepts

SQL

Python

DBT Cloud

DBT core

Snowflake

Synapse

Databricks

CI/CD

Git

Bitbucket

Jira

Mentoring

Enterprise architecture

Education

Bachelor's degree or equivalent experience

Tools

DBT Cloud

DBT core

Snowflake

Databricks

Synapse

Job description

Your Role

The Data Services team is responsible for technical design and end‑to‑end delivery of complex data‑driven solutions and data products for the enterprise. The Data Engineer, Principal will report to the Sr Manager, Data Solutions / Director. In this role you will be partnering with Enterprise Architects, Portfolio, Analytics and Data engineering teams for designing technical solutions and building data products to meet enterprise data needs. You will be responsible for driving the data product by designing and implementing cloud data lakes, data warehouse and data mart solutions.

Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow - personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high‑performing teams, getting results the right way, and fostering continuous learning.

Your Knowledge and Experience

• Requires a bachelor's degree or equivalent experience.
• Requires a minimum of 10 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 in understanding data management practices, data modelling (data vault 2.0), master data management, data integration, data architecture, data virtualization, data warehousing, data privacy and security.
• Demonstrated enthusiasm for AI and emerging technologies, with solid understanding of AI/ML concepts and hands‑on experience applying AI‑driven solutions in enterprise environments.
• Hands on experience with SQL, Python, DBT Cloud and DBT core. Expert in one or more of NoSQL and database appliances and platforms (Snowflake, Synapse, 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 (e.g., Git, Bitbucket, Jira).
• Experience in healthcare, regulated environments, or large enterprises is strongly preferred.