VP - Data Technology & Engineering Manager

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TriState Capital Bank is an independent chartered bank subsidiary of Raymond James. Headquartered in Pittsburgh, PA, TriState Capital Bank provides premier private banking, commercial banking, and treasury management products and services to corporate, institutional, and high-net-worth (HNW) clients.

Summary Of The Position

The Data Technology & Engineering Manager will lead the delivery of all data technology related solutions within an Agile framework, ensuring alignment with business priorities defined by the Product Owner. This role is responsible for building and leading a cloud‑native data platform and engineering practice that delivers trusted, governed, production‑grade datasets for analytics, AI, regulatory reporting, and partner integrations. This is a player‑coach role that is to be hands‑on enough to design and review code and pipelines, while setting strategy, roadmap, and talent standards.

Primary Functions Of The Position

• Agile Delivery Leadership : Act as the delivery lead for data engineering initiatives, working closely with the Product Owner to refine backlog items, prioritize work, and ensure timely delivery of features that meet business objectives.
• Platform Stewardship : Serve as the guardian of the organization’s Azure Data Lake platform, leveraging Data Lake and Blob storage within a medallion architecture to enable efficient data storage and processing.
• Team Coordination and Enablement : Collaborate with cross-functional teams of developers, data engineers, reporting analysts, and data governance to design, build, and continuously improve data pipelines, integration processes, and reporting solutions. Translate governance standards into code and controls (DQ rules, glossary links, lineage harvesting, RBAC/ABAC tagging); provide evidence for certification.
• Master Data (MDM) & Distribution: Implement Lean MDM in the Lakehouse for Customer and Account: entity resolution (deterministic + probabilistic), survivorship rules, and auditability. Publish Golden Records through APIM/APIs, reverse ETL to analytics/reporting platforms, and feature stores for AI/ML; synchronize with CRM/LOS.
• Delivery & Operations: Run Agile delivery: backlog prioritization, release cadence, and “definition of done” anchored in governance gates and production SLAs. Establish DataOps/SRE: end‑to‑end monitoring, runbooks, on‑call rotations, capacity planning, RCA/postmortems, and continuous improvement.
• Self-Service Enablement : Drive initiatives that empower business users through self-service analytics tools such as Power BI Cloud, ensuring data accessibility and usability across the enterprise.
• Continuous Improvement : Promote best practices in data engineering, including automation, performance optimization, and adherence to security and compliance standards.
• Stakeholder Engagement : Act as a liaison between technical teams and business stakeholders, ensuring transparency, managing dependencies, and communicating progress effectively.

Essential Skills And Abilities

• Must have strong analytical skills, with the ability to assemble and interpret data, create executive summaries, and deliver actionable business insights.
• Deep experience with Azure data stack (Data Lake Storage, Databricks/Fabric, ADF/Synapse) and enterprise SQL Server tooling (SSIS/SSRS/SSAS).
• Strong programming in Python and/or Scala/SQL; expertise in Delta Lake, schema evolution, and orchestration.
• Proven delivery of governed pipelines, DQ frameworks, metadata & lineage (Purview), and Bronze→Silver→Gold certification workflows.
• Experience implementing MDM/Golden Records (match/merge, survivorship, audit fields) and distributing via APIs/APIM and analytics tools.
• CI/CD (GitHub/Azure DevOps), Infrastructure‑as‑Code (Terraform/Bicep), and DataOps/SRE practices.
• Must be self-motivated with the ability to manage tight deadlines and ever-changing priorities.
• Strong business communication, relationship management and negotiation skills.
• Excellent problem-solving skills, strong attention to detail, and the ability to work well in a team environment.
• Strong business requirements gathering skillset.

Education And Experience Requirements

• 10–15 years in data engineering/platform roles; 5+ years leading teams as a hands‑on manager/architect.
• Financial services or regulated industry background; familiarity with privacy, retention, access controls, and audit requirements.

If you have questions about this posting, please contact [email protected]