4 days ago
Pune, IndiaStaff+
Responsibilities
- Build and scale high-quality, data-intensive platforms using data virtualization and data domain approaches.
- Design and maintain data pipelines, data lakes, data warehouses, data mesh architectures, and ETL/ELT solutions.
- Develop distributed systems that process structured and unstructured data for storage, analysis, and reporting.
- Design and optimize data processing, storage, database, OLTP, ODS, and data warehouse applications.
- Implement data federation and data virtualization architectures using Starburst/Trino and related technologies.
- Develop and integrate AI agents into data engineering workflows and enterprise software systems.
- Configure MCP servers and design MCP-compatible tools for agents to query, transform, and validate data.
- Apply RAG, vector databases, and LLMs to enterprise data use cases such as schema inference, natural-language querying, and data cataloging.
- Implement data quality and data lineage capabilities and perform database tuning.
Requirements
- 7+ years of overall experience in Big Data or enterprise-scale application development using scalable technologies.
- 5+ years of relevant technology experience implementing data-intensive solutions.
- Strong expertise in Starburst/Trino, data federation, and data virtualization architectures.
- Experience with real-time data processing and technologies including Starburst, Snowflake, and Flink is preferred.
- Strong understanding of data modeling, data warehousing, distributed systems, and structured and unstructured data.
- Experience with Spark, Starburst, Snowflake, Redshift, Hadoop, MongoDB, Oracle, Airflow, Ab Initio, and Talend or comparable solutions.
- Experience building data lakes, data warehouses, data mesh architectures, data pipelines, and ETL/ELT patterns.
- Proficiency in PL/SQL, Unix Shell scripting, SQL, database development, and database tuning.
- Experience designing OLTP, ODS, and data warehouse applications, as well as data quality and data lineage capabilities.
- Demonstrable experience designing, developing, and integrating AI agents into data engineering workflows.
- Practical knowledge of MCP server configuration, MCP-compatible tool interfaces, and MCP client-server architecture.
- Understanding of RAG principles, vector databases, advanced retrieval techniques, and LLM applications in data engineering.
- Bachelor’s or university degree, or equivalent experience.
Tech Stack
Amazon RedshiftApache AirflowApache FlinkApache HadoopApache SparkDatabricksJavaMongoDBPythonScalaSnowflakeSQLTalend
Categories
Data Engineering
About Citi
Citi is a public financial-services company offering consumer and institutional banking, credit cards, wealth management, treasury and trade solutions, and capital-markets services. It serves individuals, corporations, financial institutions, and governments in more than 160 countries and jurisdictions, earning interest and fee income from lending, payments, trading, and advisory. Founded in 1812 and headquartered in New York, it trades on the NYSE under the ticker C.