Principal Analytics Engineer Jobs
Principal Analytics Engineer jobs are open across technology, finance, healthcare, and retail, from senior analytics engineer to staff and principal levels, with specializations in data modeling, dbt, and cloud data platform architecture. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 106+ Principal Analytics Engineer jobs
FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers, advertisers, and media buyers. Powered by premium video content, robust data, and advanced technology, we’re making it easier for buyers and sellers to transact across all screens, data types, and sales channels. As a global company, we have offices in nine countries and can insert advertisements around the world.
Job Summary
Job Description Summary We are seeking an individual contributor, Operational Process Analytics & Agentic AI Strategy to lead the identification, prioritization, and strategic development of AI-driven operational transformation opportunities across the organization. This role will serve as a bridge between business operations, analytics, automation, and AI execution teams. The ideal candidate combines deep operational process expertise with advanced understanding of Agentic AI capabilities and limitations from a business and transformation lens. This leader will partner directly with senior stakeholders to evaluate operational pain points, identify high-value AI and automation opportunities, develop business cases, align priorities across organizations, and shape multi-quarter transformation roadmaps. Once initiatives are approved, this role will transition programs into execution teams while remaining accountable for strategic alignment, adoption readiness, and measurable business outcomes. Over time, this role will expand to lead AI enablement and change management efforts to ensure sustainable adoption of AI-driven workflows and decision-making across the enterprise.
Job Description
Key Responsibilities
AI Opportunity Identification & Process Transformation
- Analyze operational workflows, support models, and business processes to identify opportunities for Agentic AI, automation, and process optimization.
- Evaluate operational inefficiencies, manual dependencies, decision bottlenecks, and scalability challenges.
- Translate business problems into AI-enabled operational strategies and practical implementation opportunities.
- Assess where AI should be applied versus where traditional automation or process redesign is more appropriate.
Strategic Roadmap & Business Case Development
- Build and maintain prioritized AI transformation roadmaps aligned to organizational goals and operational priorities.
- Develop business cases including ROI analysis, operational impact, risk assessment, adoption considerations, and resource requirements.
- Partner with business leaders to balance strategic value, feasibility, implementation complexity, and organizational readiness.
- Influence prioritization decisions across multiple stakeholder groups and competing business demands.
Agentic AI Advisory & Governance
- Act as a strategic advisor to leadership on Agentic AI capabilities, risks, operating models, and implementation considerations.
- Guide leadership teams toward rational, measurable, and business-aligned AI decisions rather than trend-driven adoption.
- Evaluate AI use cases through the lens of architecture, scalability, governance, operational risk, compliance, and workforce impact.
- Act as an SME and business architect to work with Engineering and Enterprise Architecture teams to design architectural frameworks and standards.
- Help establish frameworks and standards for responsible AI adoption within operational functions.
Cross-Functional Leadership
- Partner closely with Operational Analytics, Automation & AI Development, Business Performance Analytics, Application Support, and business operations teams.
- Collaborate with technical execution teams to transition approved initiatives into delivery roadmaps with clear business objectives and success metrics.
- Facilitate alignment across business, technical, and operational stakeholders, including managing challenge and resistance constructively.
Change Management & AI Enablement
- Develop AI enablement strategies that improve organizational understanding, readiness, and adoption of AI-powered workflows.
- Partner with leadership to drive operational change management initiatives tied to AI transformation programs.
- Create communication frameworks, stakeholder engagement strategies, and adoption measurement approaches.
- Help establish long-term AI literacy and operational AI maturity across the organization.
Qualifications
Required Experience
- 8+ years of experience in operational analytics, business transformation, process optimization, management consulting, technical consulting, AI strategy, or related fields.
- Demonstrated experience identifying and driving large-scale operational improvement initiatives.
- Strong understanding of Agentic AI concepts, AI workflow orchestration, intelligent automation, and emerging AI operating models.
- Experience building business cases and influencing prioritization decisions at leadership levels.
- Proven ability to work cross-functionally across business, analytics, operations, and technical teams.
- Strong executive communication, facilitation, and stakeholder management skills.
- Comfortable operating in environments with ambiguity, evolving priorities, and constructive challenge.
Preferred Experience
- Experience in operational AI transformation, automation strategy, or enterprise AI programs.
- Familiarity with support operations, workflow systems, CRM platforms, or enterprise operational ecosystems.
- Experience leading organizational change management or transformation adoption initiatives.
- Exposure to AI governance, risk evaluation, and responsible AI frameworks.
- Experience working with global operational teams and enterprise-scale transformation programs.
Leadership Characteristics
- Strategic and pragmatic thinker who balances innovation with operational reality.
- Strong influencing skills without relying on direct authority.
- Able to challenge assumptions and guide leadership discussions with credibility and data-driven reasoning.
- Highly collaborative with the ability to translate between technical and business audiences.
- Comfortable making recommendations in rapidly evolving AI environments.
- Focused on measurable business outcomes, adoption, and scalability rather than experimentation alone.
Success Metrics
- Identification and prioritization of high-value AI transformation opportunities.
- Business impact delivered through AI-enabled operational improvements.
- Adoption and effectiveness of AI-enabled workflows.
- Executive alignment and roadmap clarity across operational AI initiatives.
- Reduction in operational inefficiencies and manual process dependencies.
- Increased organizational AI readiness and enablement maturity.
Employees at all levels are expected to:
- Understand our Operating Principles; make them the guidelines for how you do your job.
- Own the customer experience - think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services.
- Know your stuff - be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.
- Win as a team - make big things happen by working together and being open to new ideas.
- Be an active part of the Net Promoter System - a way of working that brings more employee and customer feedback into the company - by joining huddles, making call backs and helping us elevate opportunities to do better for our customers.
- Drive results and growth.
- Support a culture of inclusion in how you work and lead.
- Do what's right for each other, our customers, investors and our communities.
Disclaimer: This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.
Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.
Skills:
Business Process Transformation; Artificial Intelligence (AI); Collaboration; Conversational AI; AI Agents
Salary:
New York Pay Range: $134,677.61 - $202,016.41
Comcast intends to offer the selected candidate base pay within this range, dependent on job-related, non-discriminatory factors such as experience. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.
Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality - to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.
Education
Bachelor's Degree
While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.
Relevant Work Experience
10 Years +
FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers, advertisers, and media buyers. Powered by premium video content, robust data, and advanced technology, we’re making it easier for buyers and sellers to transact across all screens, data types, and sales channels. As a global company, we have offices in nine countries and can insert advertisements around the world.
Job Summary
Job Description Summary We are seeking an individual contributor, Operational Process Analytics & Agentic AI Strategy to lead the identification, prioritization, and strategic development of AI-driven operational transformation opportunities across the organization. This role will serve as a bridge between business operations, analytics, automation, and AI execution teams. The ideal candidate combines deep operational process expertise with advanced understanding of Agentic AI capabilities and limitations from a business and transformation lens. This leader will partner directly with senior stakeholders to evaluate operational pain points, identify high-value AI and automation opportunities, develop business cases, align priorities across organizations, and shape multi-quarter transformation roadmaps. Once initiatives are approved, this role will transition programs into execution teams while remaining accountable for strategic alignment, adoption readiness, and measurable business outcomes. Over time, this role will expand to lead AI enablement and change management efforts to ensure sustainable adoption of AI-driven workflows and decision-making across the enterprise.
Job Description
Key Responsibilities
AI Opportunity Identification & Process Transformation
- Analyze operational workflows, support models, and business processes to identify opportunities for Agentic AI, automation, and process optimization.
- Evaluate operational inefficiencies, manual dependencies, decision bottlenecks, and scalability challenges.
- Translate business problems into AI-enabled operational strategies and practical implementation opportunities.
- Assess where AI should be applied versus where traditional automation or process redesign is more appropriate.
Strategic Roadmap & Business Case Development
- Build and maintain prioritized AI transformation roadmaps aligned to organizational goals and operational priorities.
- Develop business cases including ROI analysis, operational impact, risk assessment, adoption considerations, and resource requirements.
- Partner with business leaders to balance strategic value, feasibility, implementation complexity, and organizational readiness.
- Influence prioritization decisions across multiple stakeholder groups and competing business demands.
Agentic AI Advisory & Governance
- Act as a strategic advisor to leadership on Agentic AI capabilities, risks, operating models, and implementation considerations.
- Guide leadership teams toward rational, measurable, and business-aligned AI decisions rather than trend-driven adoption.
- Evaluate AI use cases through the lens of architecture, scalability, governance, operational risk, compliance, and workforce impact.
- Act as an SME and business architect to work with Engineering and Enterprise Architecture teams to design architectural frameworks and standards.
- Help establish frameworks and standards for responsible AI adoption within operational functions.
Cross-Functional Leadership
- Partner closely with Operational Analytics, Automation & AI Development, Business Performance Analytics, Application Support, and business operations teams.
- Collaborate with technical execution teams to transition approved initiatives into delivery roadmaps with clear business objectives and success metrics.
- Facilitate alignment across business, technical, and operational stakeholders, including managing challenge and resistance constructively.
Change Management & AI Enablement
- Develop AI enablement strategies that improve organizational understanding, readiness, and adoption of AI-powered workflows.
- Partner with leadership to drive operational change management initiatives tied to AI transformation programs.
- Create communication frameworks, stakeholder engagement strategies, and adoption measurement approaches.
- Help establish long-term AI literacy and operational AI maturity across the organization.
Qualifications
Required Experience
- 8+ years of experience in operational analytics, business transformation, process optimization, management consulting, technical consulting, AI strategy, or related fields.
- Demonstrated experience identifying and driving large-scale operational improvement initiatives.
- Strong understanding of Agentic AI concepts, AI workflow orchestration, intelligent automation, and emerging AI operating models.
- Experience building business cases and influencing prioritization decisions at leadership levels.
- Proven ability to work cross-functionally across business, analytics, operations, and technical teams.
- Strong executive communication, facilitation, and stakeholder management skills.
- Comfortable operating in environments with ambiguity, evolving priorities, and constructive challenge.
Preferred Experience
- Experience in operational AI transformation, automation strategy, or enterprise AI programs.
- Familiarity with support operations, workflow systems, CRM platforms, or enterprise operational ecosystems.
- Experience leading organizational change management or transformation adoption initiatives.
- Exposure to AI governance, risk evaluation, and responsible AI frameworks.
- Experience working with global operational teams and enterprise-scale transformation programs.
Leadership Characteristics
- Strategic and pragmatic thinker who balances innovation with operational reality.
- Strong influencing skills without relying on direct authority.
- Able to challenge assumptions and guide leadership discussions with credibility and data-driven reasoning.
- Highly collaborative with the ability to translate between technical and business audiences.
- Comfortable making recommendations in rapidly evolving AI environments.
- Focused on measurable business outcomes, adoption, and scalability rather than experimentation alone.
Success Metrics
- Identification and prioritization of high-value AI transformation opportunities.
- Business impact delivered through AI-enabled operational improvements.
- Adoption and effectiveness of AI-enabled workflows.
- Executive alignment and roadmap clarity across operational AI initiatives.
- Reduction in operational inefficiencies and manual process dependencies.
- Increased organizational AI readiness and enablement maturity.
Employees at all levels are expected to:
- Understand our Operating Principles; make them the guidelines for how you do your job.
- Own the customer experience - think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services.
- Know your stuff - be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.
- Win as a team - make big things happen by working together and being open to new ideas.
- Be an active part of the Net Promoter System - a way of working that brings more employee and customer feedback into the company - by joining huddles, making call backs and helping us elevate opportunities to do better for our customers.
- Drive results and growth.
- Support a culture of inclusion in how you work and lead.
- Do what's right for each other, our customers, investors and our communities.
Disclaimer: This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.
Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.
Skills:
Business Process Transformation; Artificial Intelligence (AI); Collaboration; Conversational AI; AI Agents
Salary:
New York Pay Range: $134,677.61 - $202,016.41
Comcast intends to offer the selected candidate base pay within this range, dependent on job-related, non-discriminatory factors such as experience. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.
Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality - to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.
Education
Bachelor's Degree
While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.
Relevant Work Experience
10 Years +
Principal Analytics Engineer Jobs by Experience Level
See All 106+ Principal Analytics Engineer Jobs
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Find JobsPrincipal Analytics Engineer Job Market
Who's Hiring
Top Industries Hiring
- Consulting & Professional Services
- Insurance
- Technology & Software
- Biotechnology & Pharmaceuticals
- Manufacturing
What Employers Look For
The qualifications that appear most often in principal analytics engineer jobs.
- Advanced proficiency in SQL and at least one analytics engineering tool such as dbt
- Experience building and maintaining production-grade data models in a cloud data warehouse
- Ability to define and enforce data modeling standards and best practices across teams
- Strong communication skills for translating technical data decisions to non-technical stakeholders
- Experience with version control and software engineering workflows applied to analytics code
- Bachelor's degree in a quantitative field or equivalent experience with five or more years in analytics engineering
Tips for Your Principal Analytics Engineer Job Search
Tailor your resume to data modeling depth
Principal-level roles expect you to demonstrate ownership of modeling standards, not just individual models. Highlight decisions you made about layering strategy, schema design, or semantic layer governance, and name the specific tools and warehouses involved.
Show cross-functional influence in your portfolio
Hiring managers at this level want evidence you've shaped how analysts and data scientists consume data. Document a project where your modeling choices directly changed how a business team made decisions, and frame the outcome in business terms.
Apply early to roles that fit
Migrate Mate lists principal analytics engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by your stack before applying
Principal roles are often stack-specific. A job built around dbt Core and BigQuery is a different environment than one on Databricks and Unity Catalog. Applying only where your primary stack matches saves time and raises your interview-to-offer rate.
Prepare a modeling philosophy for the interview
Expect interviewers to ask how you decide between wide tables and normalized schemas, or how you enforce consistency across a large team. Rehearse a concise answer that reflects real trade-offs you've navigated, not just textbook definitions.
Negotiate scope alongside compensation
At the principal level, your influence over tooling decisions, team standards, and roadmap priorities is as negotiable as your title. Ask directly which decisions you'd own and where sign-off is required, so you understand actual authority before accepting.
Principal Analytics Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most principal analytics engineers?
The companies hiring the most principal analytics engineers right now include GEICO, Amazon Web Services, and Amazon, with the largest share of openings in New York, California, and Illinois, based on current listings on Migrate Mate as of November 2026. Technology, financial services, and healthcare companies account for the bulk of active postings at this level.
How many principal analytics engineer jobs are remote?
About 85% of principal analytics engineer openings are fully remote or hybrid as of November 2026, reflecting strong demand for senior analytics talent regardless of geography. Roles centered on cloud-native modeling, dbt development, and data platform strategy tend to be the most remote-friendly, while positions tied to embedded data teams in regulated industries more often require on-site presence.
How do you become a principal analytics engineer?
Start by building deep SQL and data modeling skills in a production environment, then progress through senior analytics engineering roles where you own complex model layers. Develop expertise in a major cloud warehouse and an analytics engineering tool like dbt. At the principal level, employers expect you to have set team-wide standards, mentored other engineers, and influenced data architecture decisions beyond your immediate team.
Can you get hired as a principal analytics engineer without direct principal-level experience?
Yes, candidates who demonstrate principal-level impact in a senior title can make the jump. Focus your application on outcomes that show you've already operated at that scope, such as designing a modeling framework adopted by your whole team or leading a data platform migration. A strong portfolio of architecture decisions carries more weight than the title on your last role.
What does the principal analytics engineer interview process look like?
Most processes include an initial recruiter screen, a technical take-home or live SQL and dbt exercise, and a system design round where you're asked to model a business domain from scratch. Expect at least one round with a data or engineering leader focused on your approach to standards, documentation, and cross-team influence. Final rounds often include a presentation of past work to a panel of stakeholders.
Where can I find and apply to principal analytics engineer jobs?
You can find and apply to principal analytics engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the roles available, find the ones that match your background and stack, and apply directly to each listing that fits.
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