Job
Description
About Zeta Zeta is a Next-Gen Banking Tech company that empowers banks and fintechs to launch banking products for the future. It was founded by and Ramki Gaddipati in f lagship processing platform - Zeta Tachyon - is the industry's first modern, cloud-native, and fully API-enabled stack that brings together issuance, processing, lending, core banking, fraud & risk, and many more capabilities as a single-vendor stack. 15M+ cards have been issued on our platform is actively working with the largest Banks and Fintechs in multiple global markets transforming customer experience for multi-million card portfolios. Zeta has over 1,700+ employees across the US, EMEA, and Asia, with 70%+ roles in R&D . Backed by SoftBank, Mastercard, and other investors , we raised $330M at a $2B valuation in 2025 more @ , , , About the Role In this role, you'll design robust data models using SQL, DBT and Redshift, while driving best practices across development, deployment, and monitoring. You'll also collaborate closely with product and engineering to ensure data quality and impactful delivery. Responsibilities Create optimised data models with SQL, DBT and Redshift Write functional and column level test for Models Build reports from the data models Collaborate with product to clarify requirement and create design document Get design reviewed from Architect/Principal/Lead Engineer Contribute to code reviews Set up and monitor Airflow DAGs Set up and use CI/CD pipelines Leverage Kubernetes operators for deployment automation Ensure data quality Drive best practices in Data models development, deployment, and monitoring Mentor colleagues and contribute to team growth Skills Bachelor's/Master's degree in engineering In-depth expertise in SQL and Python programming. Strong expertise in SQL for complex data querying and optimization Hands-on experience with Apache Airflow for orchestration and scheduling Solid understanding of data modeling and data warehousing concepts Experience with dbt (Data Build Tool) for data transformation and modeling Exposure to Amazon Redshift or other cloud data warehouses Familiarity with CI/CD tools such as Jenkins Experience using Bitbucket for version control Monitoring and alerting using Grafana and Prometheus Working knowledge of JIRA for agile project tracking Familiarity with Kubernetes for deployment automation and orchestration Experience and Qualifications 4-6 years of relevant experience in data engineering s/Master's degree in engineering (computer science, information systems)
