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A major healthcare organization is seeking a VP, Director of Data Engineering to define and execute the enterprise's data engineering vision. This remote position requires extensive experience in managing complex data pipelines and leading cross-functional teams. The ideal candidate has a strong background in data architecture and programming, preferably within a regulated industry. Competitive compensation and benefits are offered.
This position is 100% remote within the Bank's footprint. Employee will work full-time remotely outside of a WesBanco location (may occasionally attend in-person meetings, although primary functions are performed remotely).
Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or a related field required; Master's degree preferred.
Minimum of ten years of progressive experience in data engineering and architecture roles required, including at least five years in a leadership capacity.
Experience in the financial services industry or other highly regulated environments preferred.
SUMMARY:
The VP, Director of Data Engineering is a strategic and hands-on leadership role responsible for defining and executing the vision for enterprise data engineering, pipeline development, and platform architecture. This position leads the design, development, and operational oversight of scalable data pipelines and systems that enable data integration, analytics, reporting, and data science across the organization.
This leader ensures the delivery of secure, compliant, and high-performing data environments by guiding engineering and architecture teams through the design and operation of robust, modern data platforms. The role is critical in advancing the Bank's data maturity and driving business value through efficient data practices and infrastructure.
OTHER QUALIFICATIONS:
Extensive experience in designing and managing complex data pipelines, platform architecture, and distributed data systems required.
Strong programming and scripting skills in SQL, Python, R, and experience with ETL/ELT tools and orchestration frameworks required.
Hands-on experience with modern data platforms such as Snowflake, Databricks, Amazon Redshift, BigQuery, or similar required.
Proven success in leading and scaling cross-functional technical teams in data engineering and platform architecture required.
Proficiency in cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and hybrid cloud/on-premises architectures.
Familiarity with enterprise architecture frameworks (e.g., TOGAF), CI/CD pipelines, version control, and DevOps tools.
Knowledge of metadata management, data quality frameworks, and data lineage tooling.
Demonstrated ability to align data initiatives with business strategies and drive measurable impact.
Strong interpersonal and communication skills with the ability to influence stakeholders at all levels.
Ability to communicate effectively with technical and non-technical stakeholders.