Data Engineer

About the Role

We're looking for a Data Engineer to design, build, and maintain scalable data pipelines, ETL processes, and data models. This role includes optimizing data storage, ensuring data quality, and collaborating with cross-functional teams to deliver impactful, data-driven solutions.

Key Responsibilities

• Design, build, and maintain AI and analytics solutions on Databricks, including its native AI/ML capabilities.
• Develop AI agents and agentic workflows to automate analysis, reporting, and decision-support tasks.
• Build and curate AI-driven BI insights using Databricks Genie (Workspace) for natural-language analytics and integrate outputs with Power BI dashboards.
• Translate NBFC business problems (loan origination, credit assessment, delinquency/collections, portfolio monitoring, KYC/AML, regulatory reporting) into AI/BI solutions.
• Implement and work with the Model Context Protocol (MCP) and related tooling to connect LLMs/agents to internal data sources and enterprise tools.
• Collaborate with business, risk, and data teams to identify high-value AI use cases and deliver measurable outcomes.
• Ensure solutions adhere to data governance, security, and applicable regulatory requirements (RBI guidelines, data privacy).

Required Skills & Experience

• 4-6 years of relevant experience in AI/ML, data engineering, or BI/analytics.
• Hands-on experience with Databricks and its AI use cases (Lakehouse, notebooks, ML workflows; familiarity with Mosaic AI / Databricks AI features is a plus).
• Practical knowledge of AI and AI agents — building, deploying, and orchestrating LLM-based and agentic solutions.
• Experience generating AI-driven BI insights, including Databricks Genie / Genie Workspace for natural-language querying and Power BI for visualization and reporting.
• Working knowledge of the Model Context Protocol (MCP) and associated tools for connecting AI agents to data and applications.
• Understanding of Indian NBFC / financial services use cases and the data involved (lending, credit bureau/CIBIL data, collections, regulatory reporting).
• Strong SQL and Python; solid grasp of data modeling and pipelines.