Senior Principal Cloud Data Engineer

M&T BankWilmington, DE
1dHybrid

About The Position

This role offers a hybrid work schedule providing the opportunity for in-person collaboration at our Wilmington, DE location. Overview: The Senior Principal Cloud Data Engineer is a senior‑level individual contributor responsible for defining, building, and evolving enterprise cloud data platform capabilities in Microsoft Azure. This role provides deep technical leadership across cloud data architecture, platform engineering, and enablement, ensuring that enterprise data solutions are scalable, secure, and consistent with M&T’s data and technology strategies. The role partners closely with Enterprise Architecture and the Data organization to help define and drive the enterprise data strategy from a cloud platform perspective. In addition to influencing strategy, this role is accountable for owning and engineering the associated Azure‑based data platform capabilities that enable analytics, reporting, and data‑driven solutions across the enterprise. The position operates primarily upstream of data solution delivery, focusing on platform standards, reusable capabilities, and architectural alignment while remaining grounded in hands‑on engineering and real‑world implementation.

Requirements

  • Combined minimum of 10 years’ higher education and/or experience in systems design, management, and/or architecture
  • Thorough understanding of the system development and infrastructure lifecycle and architecture, vendor best practices, IT Service Management, and systems design

Nice To Haves

  • Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
  • Significant experience in cloud data engineering or platform engineering roles
  • Demonstrated expertise in: Azure data services and architectures Cloud‑based data integration and processing Platform‑engineering approaches for data solutions Infrastructure as Code and automation
  • Experience operating in large‑scale or regulated enterprise environments
  • Background in enterprise data platforms, analytics enablement, or data modernization
  • Familiarity with data governance, data quality, and operational data management practices

Responsibilities

  • Enterprise Cloud Data Platform Leadership Define and influence the architecture and engineering standards for enterprise cloud data platforms in Azure.
  • Serve as a senior technical authority for cloud data platform decisions, including trade‑offs across scalability, security, performance, and cost.
  • Provide technical leadership for the evolution of shared data capabilities used by analytics, reporting, and application teams.
  • Data Strategy Partnership Partner closely with Enterprise Architecture and the Data organization to:
  • Help shape and refine the enterprise data strategy,
  • Translate data strategy into actionable cloud platform capabilities,
  • Ensure cloud data platform designs align with enterprise data models, governance standards, and long‑term architectural direction.
  • Act as a technical bridge between data strategy and engineering execution.
  • Cloud Data Platform Engineering (Azure) Own the design and build‑out of core Azure‑based data platform capabilities, including but not limited to:
  • Data ingestion and integration patterns,
  • Enterprise data storage and lakehouse architectures,
  • Data processing and transformation platforms,
  • Analytics and consumption enablement patterns
  • Establish opinionated, reusable platform components and reference implementations rather than one‑off data solutions.
  • Ensure data platforms are built with automation, resilience, and security by design.
  • Standards, Patterns & Reference Architectures Develop and maintain approved reference architectures and technical patterns for cloud‑based data solutions.
  • Define standards for:
  • Data pipelines and integration approaches,
  • Storage, partitioning, and lifecycle management,
  • Access control, encryption, and data protection,
  • Monitoring, observability, and operational support
  • Ensure patterns are adoption‑ready and consumable by delivery teams.
  • Engineering Enablement Reduce delivery friction for data engineers and analytics teams by providing:
  • Clear technical guidance,
  • Reusable templates and frameworks,
  • Platform‑embedded controls and defaults
  • Promote consistency and reuse across data solutions while enabling appropriate flexibility for use‑case‑driven needs.
  • Influence adoption through engineering leadership rather than mandate.
  • Hands‑On Technical Contribution Remain actively engaged in:
  • Architecture and design reviews,
  • Proofs of concept and technical validations,
  • Platform pilots and early‑stage data initiatives
  • Validate that cloud data standards and platforms are practical, scalable, and operationally viable.
  • Provide technical mentorship to senior cloud and data engineers.
  • Cross‑Functional Collaboration Work in close partnership with:
  • Enterprise and solution architecture,
  • Data engineering, analytics, and governance teams,
  • Cloud and infrastructure engineering,
  • Security and risk management teams
  • Communicate data platform decisions and standards clearly to engineering leadership and senior technology stakeholders.
  • Ensure alignment between cloud platform capabilities and enterprise data objectives.

Benefits

  • As an employer of choice, we are proud to offer competitive benefits ranging from medical and retirement to forty hours of paid volunteer time, each year.
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