Position Description
Base pay is influenced by several factors including a candidate’s qualifications, relevant experience, and anticipated contributions to meet the needs of the business, along with internal pay equity and external market driven rates. The salary range displayed has not been adjusted for geographical location. This range has been created in good faith based on information known to Capital Blue Cross at the time of posting and may be modified in the future. Capital Blue Cross offers a comprehensive benefits packaging including Medical, Dental & Vision coverage, a Retirement Plan, generous time off including Paid Time Off, Holidays, and Volunteer time off, an Incentive Plan, Tuition Reimbursement, and more.
At Capital Blue Cross, we promise to go the extra mile for our team and our community. This promise is at the heart of our culture, and it’s why our employees consistently vote us one of the “Best Places to Work in PA.”
The Manager, Data Engineering, is responsible for leading Capital's Data Engineering team and enterprise data platform strategy. This role oversees the design, development, integration, modernization, and operation of scalable, secure, and reliable data solutions that support reporting, analytics, regulatory requirements, artificial intelligence initiatives, and business operations. The Manager establishes engineering standards, drives data modernization efforts, develops team capabilities, and partners with technology and business leaders to deliver trusted, governed, and accessible enterprise data assets.
Responsibilities and Qualifications
Data Engineering Strategy and Architecture
- 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.
Data Engineering Delivery and Team Leadership
- 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.
Data Integration, Ingestion, and Modernization
- 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.
Operational Excellence and Engineering Standards
- 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.
Data Governance, Security, 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.
Stakeholder Partnership and Planning
- 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.
Skills
- 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.
Knowledge
- 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.
- 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
- 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.
- Experience in a healthcare payer, insurance, or other regulated data environment is preferred.
Education, Certification, and Licenses
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, or equivalent relevant professional experience.
- Relevant Snowflake technical certification is strongly preferred.
- Relevant cloud, data engineering, architecture, security, or DevOps certification is preferred.
Work Environment
- This position operates in a professional office and remote-work environment and routinely uses standard office and computer equipment. The role requires regular interaction with employees, leaders, business stakeholders, vendors, and technology partners through in-person and virtual collaboration.
Physical Demands
- The physical demands described are representative of those required to perform the essential functions of the position. The role generally requires the ability to remain in a stationary position, operate a computer and other office equipment, and communicate effectively with employees and business partners. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Other
- 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.
About Us
We recognize that work is a part of life, not separate from it, and foster a flexible environment where your health and wellbeing are prioritized. At Capital you will work alongside a caring team of supportive colleagues, and be encouraged to volunteer in your community. We value your professional and personal growth by investing heavily in training and continuing education, so you have the tools to do your best as you develop your career. And by doing your best, you’ll help us live our mission of improving the health and well-being of our members and the communities in which they live.
