Data Engineer II

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.

We are seeking a Data Engineer II to design, build, and maintain reliable data pipelines and data models that power analytics and reporting across the organization. This role is a strong fit for someone with solid hands-on data engineering experience who is looking to deepen their expertise on modern cloud data platforms, take ownership of pipelines end-to-end, and continue growing technically. We're looking for someone with a positive, collaborative attitude and 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.

Design, build, and maintain scalable data pipelines to onboard and integrate data from a variety of source systems Work within the Databricks platform, applying working knowledge of the medallion architecture (bronze, silver, gold layers) to build and maintain reliable, well-structured pipelines Stay current with new Databricks capabilities (e.g., Unity Catalog, Delta Lake features, Delta Live Tables, Databricks SQL) and apply them to improve pipeline design and performance Build and maintain data models grounded in solid data fundamentals, including fact and dimension modeling Develop and optimize workloads in Google BigQuery, staying current with new BigQuery features and applying them to improve performance and query efficiency Troubleshoot pipeline issues, perform root-cause analysis, and implement fixes to ensure data reliability and quality What You'll Bring 3–5 years of experience in data engineering or a related role, with experience building and maintaining production data pipelines Hands-on experience with the Databricks platform, including working knowledge of the medallion (bronze/silver/gold) architecture Hands-on experience with Google BigQuery Solid proficiency in Python, SQL, and Git version control Understanding of data modeling fundamentals — facts, dimensions, and the ability to contribute to or build data models Ability to work across multiple source systems and adapt pipeline design to different data types and structures Preferred Qualifications Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience) Familiarity with orchestration/workflow tools (Airflow, Databricks Workflows, dbt) Exposure to CI/CD practices for data pipelines Exposure to streaming/near-real-time data concepts Familiarity with data governance and cataloging concepts (Unity Catalog, etc.) Experience working in Agile/Scrum environments What Makes You a Great Fit A collaborative team player with a positive, can-do attitude Genuinely curious, with an eagerness to learn and grow technically — on Databricks, BigQuery, and the broader data ecosystem A solid sense of ownership over the pipelines and data models you build   Write clean, maintainable code and collaborate effectively using Git version control Continuously learn emerging data engineering tools and practices, and bring ideas back to the team Partner with analytics, data science, and business stakeholders to understand requirements and deliver dependable data