Senior Principal Data Engineer Jobs
Senior Principal Data Engineer jobs are open across technology, financial services, healthcare, and media at every level from staff engineer to distinguished engineer, with specializations in data architecture, platform engineering, and real-time streaming pipelines. Find a role that fits from the openings below and apply directly.
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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.
Primary 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.
Scope of Responsibilities:
- Senior individual contributor role with enterprise‑level impact.
- Direct accountability for the design and build‑out of shared cloud data platform capabilities in Azure.
- No direct people‑management or budget ownership.
- Success measured by:
- Adoption of enterprise data platform capabilities
- Reduction in bespoke or inconsistent data solutions
- Improved scalability and reliability of data workloads
- Alignment between data strategy and platform execution
Education and Experience Required:
- 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
Education and Experience Preferred:
- 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
Location
Wilmington, Delaware, United States of America
M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $153,700.00 - $256,100.00 Annual (USD). The successful candidate’s particular combination of knowledge, skills, and experience will inform their specific compensation.
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.
Primary 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.
Scope of Responsibilities:
- Senior individual contributor role with enterprise‑level impact.
- Direct accountability for the design and build‑out of shared cloud data platform capabilities in Azure.
- No direct people‑management or budget ownership.
- Success measured by:
- Adoption of enterprise data platform capabilities
- Reduction in bespoke or inconsistent data solutions
- Improved scalability and reliability of data workloads
- Alignment between data strategy and platform execution
Education and Experience Required:
- 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
Education and Experience Preferred:
- 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
Location
Wilmington, Delaware, United States of America
M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $153,700.00 - $256,100.00 Annual (USD). The successful candidate’s particular combination of knowledge, skills, and experience will inform their specific compensation.
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Find JobsSenior Principal Data Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Genentech5
- Lila Sciences4
- Palo Alto Networks4
- Ingram Micro3
- Microsoft3
Top Industries Hiring
- Technology & Software26
- Biotechnology & Pharmaceuticals7
- Electronics & Hardware7
- Medical Devices4
- Agriculture & Farming3
What Employers Look For
The qualifications that appear most often in senior principal data engineer jobs.
- 8 or more years of experience designing and operating large-scale data platforms
- Expert-level proficiency in distributed processing frameworks such as Spark or Flink
- Deep experience with cloud data platforms including AWS, GCP, or Azure data services
- Demonstrated ability to define data architecture standards across multiple engineering teams
- Strong command of data modeling, warehousing concepts, and lakehouse patterns
- Experience mentoring senior engineers and influencing technical roadmaps at the organizational level
Tips for Your Senior Principal Data Engineer Job Search
Quantify pipeline scale on your resume
Senior principal roles attract scrutiny on scope, so replace vague language with concrete scale. Cite data volumes processed, latency targets hit, and the number of downstream teams your platform served. Reviewers at this level compare systems impact, not job duties.
Highlight cross-functional technical leadership
At the senior principal level, hiring managers want architects who align engineering, product, and analytics roadmaps. Your resume should show specific decisions you made that shaped org-wide data strategy, not just projects you delivered as an individual contributor.
Filter openings by architecture ownership signals
Job postings that mention 'define data platform strategy' or 'set engineering standards' are principal-track roles. Postings that say 'implement' or 'maintain' often get relabeled at lower levels. Read the responsibilities section carefully before investing time in an application.
Apply early to roles that fit
Migrate Mate lists senior principal data engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a system design narrative for interviews
Senior principal interviews almost always include an open-ended system design round where you defend architectural tradeoffs. Prepare a walkthrough of one real platform you designed from scratch, covering why you chose your storage layer, processing model, and observability approach.
Negotiate scope before you negotiate compensation
At this seniority, reporting structure and technical scope erode faster than base pay. Ask explicitly what the role owns versus advises, whether the principal track has a defined promotion criteria, and how many engineers will be direct or indirect stakeholders of your decisions.
Senior Principal Data Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most senior principal data engineers?
The companies hiring the most senior principal data engineers right now include Genentech, Lila Sciences, and Palo Alto Networks, with the largest share of openings in California, Washington, and Texas, based on current listings on Migrate Mate as of June 2026. Demand is strongest at companies running large internal data platforms that serve multiple product lines.
How many senior principal data engineer jobs are remote?
About 24% of senior principal data engineer openings are fully remote or hybrid as of June 2026, reflecting the hands-off-keyboard nature of architecture and strategy work at this level. Roles focused on platform governance, data mesh design, and cross-team technical standards tend to be the most remote-friendly, while roles with heavy hands-on infrastructure ownership often require on-site presence.
How do you become a senior principal data engineer?
You typically reach the senior principal level by first mastering end-to-end data platform ownership as a staff or principal engineer, then demonstrating that your architectural decisions influenced outcomes beyond your immediate team. Building a portfolio of platform designs you can defend technically, developing a reputation for cross-functional alignment, and publishing or presenting on data engineering problems accelerates recognition at this level.
Can you get hired as a senior principal data engineer with limited experience?
Direct hiring into a senior principal role with limited experience is uncommon because most job descriptions require a verified history of platform-scale ownership. The realistic path is to target principal or staff engineer roles first, take on architecture initiatives that give you cross-team scope, and build a paper trail of design decisions. Internal promotions from staff to senior principal are far more common than external hires at this level.
What does the senior principal data engineer interview process look like?
The process typically begins with a recruiter screen focused on scope and level, followed by a technical phone interview covering distributed systems and data modeling depth. Onsite or virtual rounds usually include a system design session where you architect a platform end to end, a behavioral round probing technical leadership and stakeholder influence, and a hiring manager conversation about roadmap priorities and org fit.
Where can I find and apply to senior principal data engineer jobs?
You can find and apply to senior principal data engineer jobs on Migrate Mate, which lists current openings from across the United States. Find the roles that fit your experience and target industries, then apply directly to each listing from the page.
See All 58+ Senior Principal Data Engineer Jobs
Jump back to the full list of openings and apply to any senior principal data engineer role that fits.
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