Bcbsa
Data Engineer (AI/ML)
US IL Chicago E
Sponsorship not specified$101k-$139kDetected 30 days ago
PythonCode ReviewSQLNoSQLSnowflakeDatabricksVector DatabasesAWSAzureCloud PlatformsKubernetesDevOpsMachine LearningAirflowData EngineeringLLMsRAGAI OrchestrationComplianceHIPAAHL7/FHIREHR/EMRCommunicationCollaboration
About the role
- We may ultimately pay more or less than the hiring range and t his hiring range may also be modified in the future.
Responsibilities
- The Data Engineer will design, build, and optimize scalable, secure data pipelines that power analytics and product platforms.
- 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.
- Experience designing and optimizing data architectures, including data foundations that support ML and GenAI workloads.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- 5 + years of experience in data engineering, including building and managing pipelines in cloud-based environments.
- 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.
- Hands-on experience with workflow orchestration (Airflow) and containerization (Kubernetes).
- 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.
Skills
- Use PySpark and modern cloud-based tools (Databricks, AWS Glue, EMR, Snowflake) to transform and process data efficiently.
- 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.
- Promote a culture of collaboration, innovation, and continuous learning within the engineering organization.
Compensation
- 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.
Benefits
- Experience working with healthcare datasets or knowledge of healthcare standards (HIPAA, HL7, FHIR) preferred.
This listing is sourced directly from Bcbsa's careers page and normalized into a canonical job model.