> Markdown version of [/jobs/ext/1978377-head-of-data-engineering](https://www.wearedevelopers.com/jobs/ext/1978377-head-of-data-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Head of Data Engineering - **Company:** M&T Bank - **Location:** Buffalo, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Data Architecture, Information Engineering, Data Infrastructure, Electronic Data Interchange (EDI), Metadata, Systems Development Life Cycle, Power BI, Cloud Platform System, Snowflake, Technical Debt, Generative AI, Data Management, Databricks - **Published:** August 7, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/head-of-data-engineering-buffalo-ny-usa-58834273 ## About the Role aaaE_ within a regulated financial services environment, supporting governance, lineage, controls, and reporting * Lead and grow a large team (approx. 5 direct reports and 200+ staff/contractors) with a culture of innovation, accountability, and continuous improvement Tasks * Minimum 15 years of combined education/experience, including 4 years in engineering/architecture and 11 years in technology management with people leadership * Proven leadership of large data engineering organizations in complex, regulated environments * Experience driving enterprise data modernization from strategy to execution * Deep expertise with modern data platforms (Databricks, Snowflake), data management & governance, enterprise data warehousing, BI (Power BI) and cloud data architectures * Strong understanding of data exchange, lineage, governance, metadata, and end-to-end lifecycle management * Experience engaging regulators, auditors, and risk management functions; ability to influence executive aaaaaaaa with * Proven ability to lead across strategy and hands-on execution; manage multiple complex projects * Experience with SDLC and large system enhancements/production issue resolution * Preferred: financial services or highly regulated industry experience; AI/Generative AI strategy experience; enterprise architecture leadership * Excellent collaboration and communication skills with cross-functional and executive stakeholders Key requirements * ## Description Experteer Overview In this executive role, you will define and drive the bank's enterprise data engineering vision, architecture, and modernization roadmap. You will partner with business and technology leaders to enable trusted, high-quality data across source systems, data vaults, and analytics environments, powering growth and AI-enabled innovation. You'll lead transformation programs, balance strategic thinking with hands-on problem solving, and ensure regulatory-compliant, scalable data capabilities. This is a high-impact opportunity to shape data platforms and governance for enterprise-wide data maturity and operational excellence. Compensation / Benefits * Define and advance enterprise data strategy, architecture, and modernization roadmap aligned to business priorities and long-term tech goals * Set architectural vision for scalable, secure, and compliant data capabilities; govern end-to-end data architecture across sources, lineage, integration, warehouses, and analytics * Serve as senior technical authority on data engineering and architecture; guide platform strategy, standards, and modernization efforts * Lead large-scale data transformation initiatives in active delivery, simplifying architectures and reducing technical debt * Oversee data engineering capabilities supporting critical operations and analytics; drive engineering excellence through automation and observability * Provide hands-on leadership during critical delivery and architecture challenges, collaborating with engineering teams to resolve issues and accelerate outcomes * Maintain accountability for the data and analytics portfolio, including platforms like Databricks, Snowflake, and Power BI; define modernization to cloud-based platforms * Lead evaluation and adoption of emerging technologies to keep the data ecosystem scalable and future-ready * Define how AI and Generative AI are embedded into the data engineering ecosystem; enable responsible, scalable AI adoption * Ensure data engineering operates within a regulated financial services environment, supporting governance, lineage, controls, and reporting * Lead and grow a large team (approx. 5 direct reports and 200+ staff/contractors) with a culture of innovation, accountability, and continuous improvement Tasks * Minimum 15 years of combined education/experience, including 4 years in engineering/architecture and 11 years in technology management with people leadership * Proven leadership of large data engineering organizations in complex, regulated environments * Experience driving enterprise data modernization from strategy to execution * Deep expertise with modern data platforms (Databricks, Snowflake), data management & governance, enterprise data warehousing, BI (Power BI) and cloud data architectures * Strong understanding of data exchange, lineage, governance, metadata, and end-to-end lifecycle management * Experience engaging regulators, auditors, and risk management functions; ability to influence executive stakeholders * Proven ability to lead across strategy and hands-on execution; manage multiple complex projects * Experience with SDLC and large system enhancements/production issue resolution * Preferred: financial services or highly regulated industry experience; AI/Generative AI strategy experience; enterprise architecture leadership * Excellent collaboration and communication skills with cross-functional and executive stakeholders Key requirements * ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [Data: The Deciding Factor in AI Success](https://www.wearedevelopers.com/videos/100310-data-the-deciding-factor-in-ai-success) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)