Bcbsa
Senior Manager, Data Engineering
US IL Chicago E · Senior
Sponsorship not specified$132k-$178kDetected 1 day ago
PythonCode ReviewGitSQLSnowflakeDatabricksAWSCI/CDDevOpsMachine LearningSparkData EngineeringData ScienceComplianceAgilePerformance ManagementTest AutomationHIPAALeadershipMentoringPipeline Integrity
About the role
- This is an execution-focused leadership 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 Senior Manager, Data Product Engineering is a hands-on technical leader who leads the design, development, and delivery of data products, pipelines, and analytics solutions that support BCBSA's analytics, reporting, and AI/ML workloads.
- This role leads a focused engineering team that builds and operates components of the broader data platform - using AWS, Databricks, and Snowflake as the primary stack, alongside modern orchestration, observability, and governance tooling.
- This role is expected to write production code, contribute to data architecture and design decisions, conduct code reviews, troubleshoot complex pipeline issues, and lead production support for their team's workloads - while managing and developing a team of data engineers, coordinating with vendor delivery partners, and applying the engineering standards set by leadership and broader architecture team.
- This role partners with peers across data engineering, analytics, and product teams to deliver assigned data initiatives on time, with quality, and within established platform patterns.
- Lead a team of data engineers in the design, development, and delivery of scalable data pipelines and data products using
- Strong knowledge of data governance, data quality, metadata management, lineage, access control, and production support processes.
- Working understanding of SOC 2, HIPAA, and HITRUST; experience building and delivering data engineering pipelines under regulated data handling.
Requirements
- Required 8+ years of experience in ETL, data engineering, data warehousing, or large-scale data platform development.
- Minimum 3 years of hands-on experience with AWS, Databricks and Snowflake Experience managing offshore, nearshore, vendor, or managed services delivery models.
- Strong hands-on development experience with SQL, Python, PySpark, Spark, Databricks notebooks/jobs, Snowflake SQL, and AWS data services.
- Proven experience designing and operating ETL/ELT pipelines in enterprise environments.
- Experience leading data engineering teams and mentoring engineers on technical delivery and best practices.
- Experience with CI/CD, DevOps, Git-based development, automated testing, monitoring, and deployment practices.
- Experience working in Agile, Scrum, SAFe, or product-oriented delivery environments.
- Experience with data observability, platform monitoring, FinOps, and cost optimization practices.
- Required: Certified Data Engineer Associate - Databricks or Professional level
- Required: SAFe Agilist Certification (SA) - Scaled Agile, Inc
- Required BS; or equivalent experience
- Preferred MS
- Demonstrated experience in a hands-on data engineering role with active participation in solution design, coding, code reviews, testing, deployment, and production support.
Skills
- Identify opportunities for product modernization, reusability, and engineering improvements, and bring forward recommendations.
- AWS Certified Solution Architect - Amazon Web Services (AWS) or AWS Certified Cloud Practitioner
- Knowledge Skills and Abilities
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.
Company info
- Optimize compute, storage, and workload execution across AWS, Databricks, and Snowflake for assigned workloads; apply FinOps practices in day-to-day engineering and surface cost optimization opportunities.
- Implement monitoring, alerting, observability, performance tuning, and production readiness practices for the team's data products in line with platform-wide SLAs and standards.
- Deliver data product engineering work that powers BCBSA data products across claims, member, provider, pharmacy, clinical, financial, operational, regulatory, and value-based care domains.
- Bring deep, hands-on expertise across NDW, CCL, and adjacent BCBSA enterprise data assets - applying that knowledge to data model design, source-to-target mapping, lineage, and downstream data product development.
- Partner with product managers, analytics, and data science teams to build curated datasets, semantic models, and reusable data products that support Medicare Advantage, Risk Adjustment, Stars/HEDIS, Cost of Care, and member experience use cases.
- Treat data as a product - applying product thinking to schema design, data contracts, consumer experience, documentation, versioning, and lifecycle management.
- Build data quality, lineage, and metadata capture into pipelines and data products as standard engineering practice; address data quality issues at the source rather than downstream.
- Apply HIPAA, PHI/PII protection, access control, and regulatory requirements in day-to-day engineering; partner with Privacy, Security, Compliance, and Data Governance teams on controls, reviews, and remediation for data products handling sensitive information.
- Manage day-to-day vendor relationships, delivery commitments, and performance for the team's third-party engineers and managed services partners; escalate issues and risks as appropriate.
- Coordinate offshore, nearshore, and hybrid delivery teams - driving quality, velocity, and accountability through clear assignments, code reviews, and delivery checkpoints.
- Provide input to sourcing, finance, and architecture on contract scoping, SOW review, and vendor performance - under the direction of leadership.
- Manage, mentor, and develop a team of data engineers - including performance management, coaching, technical guidance, day-to-day prioritization, and career development.
- Foster a strong engineering culture on the team grounded in code quality, operational excellence, ownership, and continuous learning.
- Contribute to engineering practices, mentoring, and knowledge sharing across the broader data engineering organization.
This listing is sourced directly from Bcbsa's careers page and normalized into a canonical job model.