Principal Engineer, Data Operations

SiriusXM; Oakland (CA); On-site; USD 180,800 - 210,000; Full time

Job summary

SiriusXM is seeking a Senior Data Operations Architect in the United States to own data operations architecture across enterprise platforms, guiding data movement, modeling, and governance. You will define scalable patterns and standards, collaborating with data engineering, analytics, and product teams to deliver reliable data assets.

You will translate complex requirements into scalable technical solutions, align KPI metrics with roadmaps, and drive governance across large-scale data

Qualifications

• Minimum of 10 years of related experience with a Bachelor’s degree; or 8 years with a Master’s; or a PhD with 6 years’ experience.
• Bachelor’s or Master’s degree in CS, IS, Data Engineering or related field.
• Principal-level experience in data operations, data engineering, analytics engineering, systems architecture, or enterprise data platform strategy.
• Expert command of the modern data stack, including Snowflake, dbt, Git, orchestration tools, data modeling and metric governance, CI/CD practices, testing frameworks, and semantic layer platforms.
• Demonstrated ability to define technical strategy, architecture standards, and scalable implementation patterns across complex enterprise data ecosystems.
• Proven ability to influence cross-functional analytics, product, engineering, and business stakeholders through technical strategy, architecture recommendations, and data-driven decision making.
• Experience mentoring senior analysts, engineers, or technical partners and raising technical quality across teams without direct people-management accountability.
• Excellent written and verbal communication skills, with a passion for making data accessible, actionable, and trusted at enterprise scale.
• Must have legal right to work in the U.S.

Responsibilities

• Serve as principal technical owner for Data Operations architecture, standards, and best practices across enterprise data platforms.
• Set the technical direction for data operations capabilities that support reliable, scalable, secure, and efficient data movement and processing across the organization.
• Define and evolve scalable Snowflake, dbt, semantic layer, and KPI architecture patterns that enable trusted, governed, and performant data assets.
• Lead critical design decisions for large-scale data models, metric standardization, semantic architecture, and data quality frameworks that support business and product outcomes.
• Partner with data engineering, product, analytics, and business stakeholders to translate complex requirements into scalable technical solutions and architecture recommendations.
• Drive technical alignment with the product roadmap and vision by ensuring KPI metrics, data models, and semantic definitions are well-defined, actionable, and reusable.
• Establish and advance technical standards for dbt, testing frameworks, CI/CD, Git workflows, orchestration, documentation, and operational excellence.
• Resolve complex DataOps and data architecture issues across large-scale ecosystems, including streaming, podcasting, satellite, publisher, and advertiser use cases.
• Review and guide the development of data pipeline requirements, process models, architectural recommendations, and reusable implementation patterns.
• Provide technical leadership, coaching, and mentorship to analysts, engineers, and cross-functional partners without direct performance-management responsibility.
• Create formal networks with key technical and business decision makers to influence enterprise data strategy, platform evolution, and long-term DataOps capabilities.
• Manage and analyze large-scale data volumes (1+ PB) across complex ecosystems that power streaming, podcasting, satellite, publisher, and advertiser use cases.
• Define and champion engineering standards, design principles, governance practices, and reusable patterns for data operations.
• Guide and mentor engineers and technical leaders across a wide range of audiences, raising technical judgment and operational excellence throughout the organization.
• Represent the organization’s data operations capabilities with senior stakeholders and, when appropriate, external technical communities.

Skills

Leadership

Mentoring

Cross-functional collaboration

Data modeling

KPI governance

Data quality

Communication

Strategic thinking

Problem solving

Education

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field

Tools

Snowflake

dbt

Git

Orchestration tools

Semantic layer

Job description

Overview

Who We Are SiriusXM and its brands (Pandora, SiriusXM Media, AdsWizz, Simplecast, and SiriusXM Connect) are leading a new era of audio entertainment and services by delivering the most compelling subscription and ad-supported audio entertainment experience for listeners—in the car, at home, and anywhere on the go with connected devices. Our vision is to shape the future of audio, where everyone can be effortlessly connected to the voices, stories and music they love wherever they are. This is a place where diverse talent comes to share authentic stories and insights through leading programming and technology. SiriusXM Media is the gateway for marketers to the largest digital audio advertising ecosystem in North America, spanning Pandora, SiriusXM, AdsWizz, Studio Resonate, and a broad content network with exclusive monetization partnerships. Reaching more than 150 million listeners each month, SiriusXM Media enables marketers to create, plan, buy and measure across its audio universe.

What You’ll Do

• Serve as the principal technical owner for Data Operations architecture, standards, and best practices across enterprise data platforms.
• Set the technical direction for data operations capabilities that support reliable, scalable, secure, and efficient data movement and processing across the organization.
• Define and evolve scalable Snowflake, dbt, semantic layer, and KPI architecture patterns that enable trusted, governed, and performant data assets.
• Lead critical design decisions for large-scale data models, metric standardization, semantic architecture, and data quality frameworks that support business and product outcomes.
• Partner with data engineering, product, analytics, and business stakeholders to translate complex requirements into scalable technical solutions and architecture recommendations.
• Drive technical alignment with the product roadmap and vision by ensuring KPI metrics, data models, and semantic definitions are well-defined, actionable, and reusable.
• Establish and advance technical standards for dbt, testing frameworks, CI/CD, Git workflows, orchestration, documentation, and operational excellence.
• Resolve complex DataOps and data architecture issues across large-scale ecosystems, including streaming, podcasting, satellite, publisher, and advertiser use cases.
• Review and guide the development of data pipeline requirements, process models, architectural recommendations, and reusable implementation patterns.
• Provide technical leadership, coaching, and mentorship to analysts, engineers, and cross-functional partners without direct performance-management responsibility.
• Create formal networks with key technical and business decision makers to influence enterprise data strategy, platform evolution, and long-term DataOps capabilities.
• Manage and analyze large-scale data volumes (1+ PB) across complex ecosystems that power streaming, podcasting, satellite, publisher, and advertiser use cases.
• Define and champion engineering standards, design principles, governance practices, and reusable patterns for data operations.
• Guide and mentor engineers and technical leaders across a wide range of audiences, raising technical judgment and operational excellence throughout the organization.
• Represent the organization’s data operations capabilities with senior stakeholders and, when appropriate, external technical communities.

What You’ll Need

• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or a PhD with 6 years’ experience; or equivalent experience.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Principal-level experience in data operations, data engineering, analytics engineering, systems architecture, or enterprise data platform strategy.
• Expert command of the modern data stack, including Snowflake, dbt, Git, orchestration tools, data modeling and metric governance, CI/CD practices, testing frameworks, and semantic layer platforms.
• Demonstrated ability to define technical strategy, architecture standards, and scalable implementation patterns across complex enterprise data ecosystems.
• Deep expertise in dimensional modeling, metric standardization, semantic architecture design, governed KPI frameworks, and data quality practices.
• Demonstrated success resolving critical technical issues and shaping broad architectural or design decisions.
• Proven ability to influence cross-functional analytics, product, engineering, and business stakeholders through technical strategy, architecture recommendations, and data-driven decision making.
• Experience mentoring senior analysts, engineers, or technical partners and raising technical quality across teams without direct people-management accountability.
• Track record of anticipating business or technology challenges and introducing meaningful process, product, service, or platform improvements.
• Demonstrated ability to guide and mentor engineers and technical leaders without relying on direct people-management authority.
• Excellent written and verbal communication skills, with a passion for making data accessible, actionable, and trusted at enterprise scale.
• Must have legal right to work in the U.S.

Compensation and Equal Opportunity Our compensation range is considered along with factors such as experience and geographic location. Base salary for this position is expected to be in the range of $180,800 to $210,000, and may be eligible for discretionary incentives. SiriusXM is an equal opportunity employer that does not discriminate on the basis of race, creed, color, religion, national origin, disability, sex, or any other protected characteristic. This description reflects the current needs of the business and may be modified as necessary.