Data Engineer, Principal

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.

#LI-FB1

Your Work

In this role, you will

• 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.
• 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 (e.g., Snowflake, Databricks, Synapse) with a focus on performance, scalability, reliability, and cost efficiency.
• 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.
• 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.
• Identify performance bottlenecks, reliability risks, and optimization opportunities across data platforms and workflows.
• 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.

Your Work

In this role, you will

• 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.
• 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 (e.g., Snowflake, Databricks, Synapse) with a focus on performance, scalability, reliability, and cost efficiency.
• 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.
• 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.
• Identify performance bottlenecks, reliability risks, and optimization opportunities across data platforms and workflows.
• 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.

Skills

Agile Programming Methodologies, Architectural Design, Artificial Intelligence (AI), Atlassian JIRA, Best Practices, Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Data Management, Data Mart, Data Modeling, Data Quality, Data Warehousing, Database Extract Transform and Load (ETL), Dimensional Modeling, Ecosystems, Embedded Systems, Emerging Technology, Enterprise Architecture, Git, Healthcare, Information/Data Security (InfoSec), Leadership, Machine Tool, Master Data Management (MDM), Mentoring, Multiplatform/Cross-Platform, Portfolio Analysis, Privacy Controls, Product Design, Product Development, Source Code/Configuration Management (SCM), Structured Data, Technical Delivery, Technical Leadership, Technical/Engineering Design, Thought Leadership, Use Cases, Virtualization

About the Company

Blue Cross and Blue Shield Association

At the Blue Cross and Blue Shield Association (BCBSA), we provide business strategy, technical support and consulting expertise to 36 Blue Cross and Blue Shield companies across the nation, employing more than 1,000 of the best strategic thinkers in the industry.

We are a Brand manager that sets quality control standards for the 36 independent companies that use the Blue Cross and Blue Shield Brands, and we serve as a trade association that represents these Blue companies. It is through our involvement that the Blues companies share a united vision and strategy while also benefiting from the local strength of all member companies.

Company Size

2,000 to 2,499 employees

Industry

Insurance

Founded

0

Website

https://www.bcbs.com/about-us/careers