Description:

​Cisco is hiring a Data Engineer for its IT Data team based in Bangalore and Hyderabad. Positioned within the Corporate Functional Data IT division, this team builds end-to-end platforms and AI-driven services to support Sales insights and global financial reporting. In this position, you will collaborate with Senior Data Engineers to develop, secure, and maintain scalable data processing pipelines. The daily scope balances traditional data warehousing architecture with modern cloud data mesh pipelines—requiring you to write clean ETL/ELT transformation code, build automated testing and data quality reporting suites, orchestrate real-time streaming, and design self-healing automation frameworks to prevent processing failures.

​Key Technologies:

​Snowflake, Informatica, dbt, Snowflake DMF, Kafka, Unix shell Script, Python, SQL

​Requirements:

• ​Formal Bachelor’s degree in Engineering, Technology, or a closely related quantitative technical field.
• ​4–8 years of professional hands-on experience designing, modeling, and scaling Data Warehousing (DWH) solutions.
• ​Specialized development and administration expertise on modern cloud data warehouses, specifically Snowflake.
• ​High proficiency engineering end-to-end data transformation pipelines using Informatica and dbt (data build tool).
• ​Direct hands-on experience implementing data quality validations, monitoring metrics, and executing data observability practices utilizing Snowflake DMF (Data Metric Functions) or matching data quality frameworks.
• ​Practical engineering experience streaming data streams and managing message queues utilizing Kafka.
• ​Strong, versatile scripting and coding capabilities using Python for automation, Unix Shell Scripting for system automation, and advanced SQL for relational data modeling and querying.
• ​Foundational experience designing, debugging, and maintaining real-time data integration systems.
• ​Solid knowledge of enterprise data governance, column/row-level security, compliance tracking, and data profiling practices.
• ​Exposure to utilizing AI/ML frameworks, predictive/prescriptive analytics models, or Large Language Models (LLMs) to enhance raw data layers.
• ​Experience working within Agile sprint paradigms; holding a SAFe Agilist certification is a distinct advantage.
• ​High commitment to software quality control, providing detailed unit test results/reports, conducting peer reviews, and communicating clearly within a highly collaborative team structure.