Software Development Engineer, Big Data

Zillow
Mexico CityPosted 14 April 2026

Job Description

About the team The Customer 360 DE team builds and maintains customer-level data products that create a comprehensive view of customer identity, engagement, journey, and outcomes. About the role In this role, you will design and develop scalable data pipelines that process petabytes of data and transform it into fast, reliable datasets used by analysts, data scientists, AI teams, and product managers to drive decisions and power models. This is an opportunity to join a newly formed team doing foundational work that is central to Zillow’s super app strategy. You Will Get To Design, build, and maintain large-scale data pipelines that process high-volume customer data. Deliver fast, reliable, production-quality datasets for analytics, AI, and product use cases. Partner with analysts, data scientists, AI teams, and product managers to support decision-making and model development. Develop data solutions that scale to billions of rows and petabyte-level workloads. Improve deployment, monitoring, and reliability across data systems. Translate business requirements into clean, evolvable data models. Use modern data technologies such as Spark, SQL, Python, Kafka, and Airflow to build robust solutions. Help shape foundational capabilities for a new team supporting Zillow’s super app strategy. This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions. In addition to a competitive base salary and benefits, this position is also eligible for equity awards based on factors such as experience, performance and location. Who you are Bachelor’s degree or higher in Computer Science or a related field. 3 years of experience building and maintaining data-intensive applications. Experience developing sophisticated, production-grade data pipelines that scale to billions of rows and petabyte-scale workloads. Strong experience with modern data technologies such as Spark , Kafka and Airflow. Strong programming skills in Python, Java, or Scala. Extensive SQL experience and strong data modeling skills, with the ability to translate business requirements into scalable datasets. Excellent interpersonal skills and a passion for collaborating across organizational boundaries. Here at Zillow - we value the experience and perspective of candidates with non-traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences. Get to know us At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company that's reshaping an industry and helping more people make home a reality. Zillow is honored to be recognized among the best workplaces in the country. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025 , and included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow. No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together. Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, p ... (truncated, view full listing at source)
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