Analytics Engineer

We are seeking an experienced Analytics Engineer to join our team in Mumbai. This full-time role is crucial for owning and optimizing the end-to-end data structuring layer across Apollo Finvest. You will transform vast amounts of raw, unstructured, and semi-structured data, including SMS, device, bureau, and app data, into clean, standardized, and analysis-ready datasets. These structured datasets will be instrumental in powering critical functions such as risk analytics, fraud detection, marketing insights, collections strategy, and policy decisioning.

Key responsibilities include designing and maintaining robust data pipelines using AWS native services, processing and categorizing unstructured data (especially financial SMS), and implementing feature creation logic provided by our Risk and Data Science teams. You will develop reusable feature layers, maintain a feature store, and work extensively with lending-specific data, including bureau, SMS-derived financial variables, account aggregator, and bank transaction datasets. Automation of data ingestion and feature refreshes, along with building analytics-ready datasets for dashboards and self-serve data access, are core components of this role. Close collaboration with data science, tech, product, and business teams is essential to ensure high data quality and enable faster, more accurate decision-making.

The ideal candidate will possess 2-6 years of experience in Data Engineering or Analytics Engineering within the fintech domain, with strong proficiency in Python and SQL. Experience handling unstructured data, building data pipelines, strong database design and data modeling skills, and the ability to thrive in a startup environment are required. Familiarity with modern data platforms like Snowflake, Google BigQuery, or Amazon Redshift is a plus. Experience in the lending/NBFC/fintech domain, working with bureau, SMS, device, or banking data, and knowledge of streaming technologies are highly preferred.