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 2015.
Our flagship 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. 20M+ cards have been issued on our platform globally.
Zeta is actively working with the largest Banks and Fintechs in multiple global markets transforming customer experience for multi-million card portfolios.
Zeta has over 1700+ employees - with over 70% roles in R&D - across locations in the US, EMEA, and Asia. We raised $280 million at a $1.5 billion valuation from Softbank, Mastercard, and other investors in 2021.
About the Role
As a Data Engineer II, you will play a crucial role in developing, optimizing, and managing several large data lakes and data warehouses, comprising data from multiple disparate sources.
Responsibilities
Data Pipeline OperationsDesign, build, and maintain robust and scalable data pipelines to ingest, transform, and deliver structured and unstructured data from multiple sources.Ensure high-quality data by implementing monitoring, validation, and error-handling processes.Platform Engineering & OptimizationCreate and update data models to represent the structure of the data.Design, implement, and maintain database systems. Optimize database performance and ensure data integrity. Troubleshoot and resolve database issues.Build and manage data warehouses for storage and analysis of large datasets.Collaborate on data modeling, schema design, and performance optimization for large-scale datasets.Data Quality and Governance: Implement and enforce data quality standards. Contribute to data governance processes and policies.Scripting and Programming: Develop and automate data processes through programming languages (e.g., Python, Java, SQL). Implement data validation scripts and error handling mechanisms.Version Control: Use version control systems (e.g., Git) to manage codebase changes for data pipelines.Monitoring and Optimization: Implement monitoring solutions to track the performance and health of data systems. Optimize data processes for efficiency and scalability.Cloud Platforms: Work with cloud platforms (e.g., AWS, Azure, GCP) to deploy and manage data infrastructure. Utilize cloud-based services for data storage, processing, and analytics.Security: Implement and adhere to data security best practices. Ensure compliance with data protection regulations.Troubleshooting and Support: Provide support for data-related issues and participate in root cause analysis.Skills
Expertise in data modeling, database design, and data warehousing. Proficient in SQL and programming languages such as Python, Java, or Scala.Experience with big data technologies such as Hadoop, Spark, and Kafka.Cloud-native architecture expertise (AWS, GCP, or Azure), including containerization (Docker, Kubernetes) and infrastructure-as-code (Terraform, CloudFormation).Experience and Qualification
Bachelor's/master's degree in engineering (computer science, information systems) with 3-5 years of experience in data engineering, BI engineering, and data warehouse development.Excellent command on SQL and one or more programming languages, preferably Python or Java.Knowledge of Flink, Airflow, Apache Spark, DBT, Athena / PrestoExperience working with Kubernetes.
