The Data Engineer will design, build, and optimize scalable, secure data pipelines that power analytics and product platforms. For this role specifically, the focus will be on Machine Learning (ML) and Generative Artificial Intelligence (GenAI) workloads, while contributing to innovation and ensuring compliance with healthcare industry standards. This role is expected to provide strong hands-on technical expertise, collaborate across teams, and contribute to architecture decisions that align engineering practices with organizational goals.
Job Description
Design, build, and maintain reliable, high-performance data pipelines for large-scale structured and unstructured healthcare data.
Use PySpark and modern cloud-based tools (Databricks, AWS Glue, EMR, Snowflake) to transform and process data efficiently.
Support ingestion, transformation, and validation processes that ensure data consistency, integrity, and availability.
Partner with Data Architects, Data Scientists, and Analysts to translate business needs into scalable engineering solutions.
Collaborate with platform and DevOps teams to deploy, scale, and monitor data pipelines using Airflow and Kubernetes.
Participate in code reviews, documentation, and continuous improvement efforts across the engineering team.
Implement and maintain data validation frameworks to ensure pipeline accuracy and completeness.
Contribute to best practices in version control, metadata management, and reproducibility.
Stay current with emerging technologies in data engineering and cloud computing, recommending improvements to existing infrastructure.
Participate in performance tuning, cost optimization, and scaling strategies for cloud-based data systems.
Identify automation opportunities to streamline ETL/ELT processes and reduce operational overhead.
Share knowledge and mentor junior team members on tools, techniques, and best practices.
Promote a culture of collaboration, innovation, and continuous learning within the engineering organization.
Support compliance with SOC 2, HIPAA, and GDPR by adhering to established data privacy and security practices.
The posting range for this position is:
100,800.00 - 138,600.00Required Education, Certifications and Experience:
Education:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Experience:
- 5+ years of experience in data engineering, including building and managing pipelines in cloud-based environments.
Knowledge Skills and Abilities
- Experience with building and operationalizing the data foundations that support machine learning and generative AI use cases, including feature pipelines, training/inference data preparation, and retrieval-ready datasets (e.g., embeddings and vector stores)
- Familiarity with GenAI skills and adjacent tooling (foundation models, prompt engineering, RAG, embeddings/vector databases, and GenAI orchestration frameworks).
- Hands-on experience with AWS AI/ML and data services, including Amazon Bedrock, Bedrock Agent Core, SageMaker, Glue, and EMR.
- Experience designing and optimizing data architectures, including data foundations that support ML and GenAI workloads.
- Hands-on experience with workflow orchestration (Airflow) and containerization (Kubernetes).
- Hands-on technical expertise, cross-team collaboration, and contributing to architecture decisions
- Proficiency in Python, SQL, and distributed data frameworks (PySpark, Databricks, AWS Glue, EMR).
- Working knowledge of cloud platforms (AWS or Azure) and data warehouses (Snowflake).
- Familiarity with NoSQL and relational databases, as well as data modeling best practices.
- Strong analytical, problem-solving, and communication skills.
- Understanding of compliance frameworks (SOC 2, HIPAA) and secure data management principles.
- Experience working with healthcare datasets or knowledge of healthcare standards (HIPAA, HL7, FHIR) preferred.
#LI_HYBRID
The posted salary range is the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the hiring range and this hiring range may also be modified in the future. A candidate’s position within the hiring range may be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, relevant experience, skills, seniority, performance, shift, travel requirements, and business or organizational needs. This job is also eligible for annual bonus incentive pay.
We offer a comprehensive package of benefits including paid time off, 11 holidays, medical/dental/vision insurance, generous 401(k) matching, lifestyle spending account and many other benefits to eligible employees.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 5+ years of experience in data engineering, building and managing cloud-based pipelines
- Proficiency in Python
- Proficiency in SQL
- Experience with PySpark and distributed data frameworks
- Experience with Databricks, AWS Glue, or EMR
- Experience with Snowflake or data warehouse technologies
- Experience with workflow orchestration (Airflow) and containerization (Kubernetes)
- Hands-on experience with AWS AI/ML and data services (Amazon Bedrock, Bedrock Agent Core, SageMaker)
- Experience building and operationalizing ML/GenAI data foundations (feature pipelines, training/inference data, embeddings/vector stores)
- Familiarity with GenAI tooling (foundation models, prompt engineering, RAG, embeddings, vector databases)
- Working knowledge of cloud platforms (AWS or Azure)
- Familiarity with NoSQL and relational databases and data modeling best practices
- Understanding of compliance frameworks and secure data management (SOC 2, HIPAA, GDPR)
- Experience working with healthcare datasets or knowledge of healthcare standards (HIPAA, HL7, FHIR)
What We Do
Blue Cross Blue Shield Association is a national federation of 34 independent, community-based and locally operated Blue Cross and Blue Shield companies that collectively provide health care coverage for one in three Americans. BCBSA provides health care insights through The Health of America Report series and the national BCBS Health Index.
