Manager, Data Engineering

Capital Blue Cross is a healthcare organization focused on improving the health and well-being of its members and communities. The Manager, Data Engineering, leads the Data Engineering team and enterprise data platform strategy, overseeing scalable data solutions, modernization, governance, security, and operational reliability. The role also partners with business and technology stakeholders to deliver trusted data assets for reporting, analytics, regulatory requirements, artificial intelligence initiatives, and business operations.

Responsibilities:

• Provide leadership for the design, implementation, operation, and continuous improvement of Capital's enterprise data engineering capabilities
• Establish current and forward-looking technical direction, architecture standards, integration efficiencies and engineering practices supporting Snowflake and other enterprise data platforms to drive enhanced platform capabilities in partnership with stakeholders and business areas for meeting strategic objectives
• Lead, coach, and develop a team of Data Engineers responsible for data platform delivery, operational support, modernization initiatives, and production reliability in cloud data engineering best practices
• Establish performance expectations, technical standards, and development plans that promote continuous learning and engineering excellence that meets or exceeds corporate defined objectives
• Manage team workload, resource allocation, priorities, and delivery commitments to ensure timely and high-quality outcomes
• Provide technical leadership through solution reviews, design guidance, code reviews, and engineering governance processes
• Lead the design, implementation, and evolution of enterprise data ingestion, integration, transformation, and data delivery frameworks
• Establish reusable integration patterns supporting batch, API-based, file-based, streaming, event-driven, and other modern data exchange methods
• Guide modernization efforts to simplify, automate, migrate or consolidate legacy data warehouse, integration, and reporting technologies
• Develop and execute roadmaps in collaboration with stakeholders that support enterprise data platform adoption, onboard new data domains and build scalable capabilities with reduced technical debt
• Establish and maintain engineering standards covering source control, testing, deployment, monitoring, documentation, release management, and production support
• Establish and monitor operational metrics to ensure reliable enterprise data platforms availability and continuous improvement opportunities identified, prioritized and implemented. Execute on identified corrective actions
• Promote the effective use of automation and approved AI-assisted development capabilities to improve engineering productivity and quality
• Partner with Data Governance, Security, and business stakeholders to incorporate data quality, metadata, lineage, stewardship, privacy, and access controls into engineering solutions
• Ensure compliance with enterprise requirements related to data protection, regulatory obligations, auditability, retention, and appropriate use of sensitive information
• Support the delivery of governed, trusted, and documented data assets for enterprise reporting, analytics, applications, and artificial intelligence initiatives
• Develop and maintain the Data Engineering roadmap, aligning technology priorities with business, regulatory, operational, and strategic objectives
• Partner with business leaders, technology teams, vendors, and data stakeholders to understand requirements, establish priorities, evaluate tool selections and deliver sustainable data solutions
• Provide visibility into projects SDLC gates and communicate complex technical concepts, risks, tradeoffs, and recommendations to technical and non-technical audiences
• May be required to provide leadership or escalation support outside standard business hours for significant production incidents, releases, or business-critical data delivery issues
• Completes other responsibilities and assignments as directed

Requirements:

• Demonstrated ability to lead and develop a technical Data Engineering team, including coaching, work assignment, quality review, delivery accountability, and skills development
• Strong ability to establish and operationalize engineering standards, reusable patterns, delivery controls, and production-support practices
• Strong technical and architectural judgment concerning the application of Snowflake capabilities within a broader enterprise data environment
• Strong communication skills, including the ability to explain complex technical issues, architectural decisions, tradeoffs, risks, costs, and investment needs in clear business terms
• Ability to manage multiple complex initiatives and shifting priorities across modernization, operations, technical debt, regulatory delivery, and business demand
• Ability to manage multiple priorities, balance strategic initiatives with operational responsibilities, and deliver results in a complex environment
• Strong collaboration and relationship-building skills across business and technology teams
• Advanced knowledge of Snowflake architecture and capabilities, including data ingestion, transformation, modeling, governed data sharing, security, workload management, performance optimization, monitoring, automation, interoperability, and cost-aware design
• Strong understanding of modern cloud and hybrid data architectures, including centralized, distributed, virtual, federated, shared, and API-enabled approaches
• Modern data integration approaches, including batch, incremental, change data capture, API-based, file-based, streaming, event-driven, virtual, federated, and governed data-sharing patterns
• Strong understanding of automated testing, source control, CI/CD process, environment and release management
• Seven (7) or more years of progressive experience in data engineering, data integration, data warehousing, or enterprise data platform delivery
• Three (3) or more years of experience leading technical teams, including coaching, performance management, and delivery accountability
• Demonstrated experience designing, implementing, and operating production data solutions on Snowflake and applying Snowflake capabilities beyond basic data storage, SQL development, and traditional warehouse workloads
• Experience establishing engineering standards, automated delivery practices, data quality controls, monitoring, and production reliability
• Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, or equivalent relevant professional experience
• Knowledge of healthcare payer data, healthcare data standards, and enterprise SaaS integrations preferred
• Knowledge of WhereScape or comparable data automation and data engineering frameworks is preferred
• Experience in a healthcare payer, insurance, or other regulated data environment is preferred
• Relevant Snowflake technical certification is strongly preferred
• Relevant cloud, data engineering, architecture, security, or DevOps certification is preferred