Data Engineer Senior

About the job

Overview: At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges.

Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.

You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally.

Come make an impact every day at Zebra.

What We're Looking For: We are seeking a Senior Data Engineer to lead the technical direction of our data engineering practice while remaining deeply hands-on. This is a role for someone who has built and owned production data pipelines end-to-end, thrives on solving complex data architecture problems, and brings the leadership presence to guide and grow a team of engineers. We're looking for someone with a strong technical foundation, a positive and collaborative attitude, and a genuine curiosity to learn and adopt new technologies as the data landscape evolves — including staying current with the latest capabilities on both Databricks and Google BigQuery.. - What You'll Do

- Lead the technical direction of the data engineering team — setting standards, guiding design decisions, and reviewing the team's work for quality and scalability

- Design, build, and maintain new, scalable data pipelines to onboard and integrate data from a wide variety of source systems

- Work extensively within the Databricks platform, applying strong command of the medallion architecture (bronze, silver, gold layers) to build and evolve reliable, well-structured pipelines

- Stay current with new Databricks capabilities (e.g., Unity Catalog, Delta Lake features, Delta Live Tables, Databricks SQL, workflow/orchestration updates) and proactively apply them to improve pipeline design, governance, and performance

- Design and build new data models grounded in solid data fundamentals, including fact and dimension modeling

- Own and optimize workloads in Google BigQuery, staying current with new BigQuery features (e.g., BQML, materialized views, storage/compute optimizations, new SQL capabilities) and applying them to improve performance, cost efficiency, and scalability

- What You'll Bring

- 7–10 years of experience in data engineering, with a demonstrated track record of building and owning production-grade pipelines end-to-end

- Proven experience leading a team on technical matters — architecture decisions, code reviews, and mentorship

- Strong, hands-on experience with the Databricks platform, including practical, working knowledge of the medallion (bronze/silver/gold) architecture and demonstrated awareness of new/evolving Databricks features

- Strong, hands-on experience with Google BigQuery, including demonstrated awareness and adoption of new BigQuery features

- Hands-on proficiency in Python, SQL, and Git version control

- Solid grounding in data modeling fundamentals — facts, dimensions, and the ability to design new data models from the ground up

- Demonstrated ability to build pipelines across diverse and evolving source systems

- Preferred Qualifications

- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience)

- Cloud certification(s) — Databricks Certified Data Engineer, Google Cloud Professional Data Engineer, or equivalent

- Experience with orchestration/workflow tools (Airflow, Databricks Workflows, dbt)

- Experience with CI/CD for data pipelines (Git-based deployment, testing frameworks for data)

- Exposure to streaming/near-real-time pipelines (Kafka, Pub/Sub, Structured Streaming)

- Experience with data governance, cataloging, and lineage tools (Unity Catalog, Collibra, etc.)

- Experience working in Agile/Scrum delivery environments

- Prior experience as a technical lead, team lead, or engineering manager (even informally)

- What Makes You a Great Fit

- A natural technical leader with a collaborative, can-do attitude

- Genuinely curious, with a strong appetite for learning and adopting new technologies as they emerge — on both Databricks and BigQuery, and the wider data ecosystem

- An ownership mindset — you see pipelines and data models through from design to production, and take pride in getting the details right

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- Mentor and coach team members on technical best practices, pipeline design, and code quality

- Continuously evaluate emerging data engineering tools and technologies across the broader data ecosystem, and bring recommendations back to the team

- Partner closely with analytics, data science, and business stakeholders to translate requirements into robust, reliable data solutions

Benefits: We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success.

Job Posting Statement: To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.

AI Technology Statement: Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However, every decision regarding interviews and hiring is made by our dedicated team, because we believe people make the best decisions about people. For more on how we use technology in hiring and how we process applicant data, see our Zebra Privacy Policy .