We are looking for a Data Engineer with 1-3+ years of experience to create a new age Data Platform from ground up.

You will be responsible for building scalable, secure, and efficient data pipelines that connect our Loan Origination System (LOS), Loan Management System (LMS), CRM, field collections apps, and external APIs (e.g., credit bureaus, Aadhaar, PAN verification) to support analytics, decisioning, reporting, and compliance.

You will work cross-functionally with the credit, risk, collections, and technology teams to ensure data availability, integrity, and real-time accessibility across the enterprise.

Education : Bachelor or above in Computer Science/Application Experience : Minimum 3 years of experience in below items : Projects : ETL pipeline, BI / Dashboard development, Database Management (as member of Data Governance team), ingesting and maintaining unstructured data like documents, images, videos, etc.

Tools : ETL tools like Talend or similar, SQL, Spark/Python, Technology : Cloud based platforms like Azure or similar, Distributed data base like HDFS, Spark clusters, RDBMS

Key Responsibilities :

1. Data Pipeline Development :

- Build, schedule, and maintain ETL/ELT pipelines to ingest data from internal systems and external sources (bureaus, Colending partners, third party vendors, etc.

- Clean, normalize, and transform raw data into analytics-ready formats using SQL, Python, and Spark.

2. Data Warehousing :

- Design and maintain a centralized data warehouse on PostgreSQL/MySQL, Redshift, or cloud data platforms (e.g., Snowflake, DataBricks).

- Ensure historical tracking, schema versioning, and optimal performance for BI tools and analytics.

3. Data Quality & Monitoring :

- Set up monitoring, alerting, and validation checks for data accuracy, latency, and pipeline failures.

- Work with business users to understand and address data quality issues.

4. Data Governance & Security :

- Implement role-based access, audit logs, and data encryption mechanisms.

- Ensure data handling complies with RBI/NBFC regulations for PII and f inancial records.

5. Automation & Scheduling :

- Use workflow orchestration tools like Airflow, Cron, or Cloud Functions to schedule batch and real-time pipelines.

- Automate reporting feeds and data sync to Power BI, Excel dashboards, or external stakeholders.

6. Collaboration & Support :

- Work closely with Data Scientists, Business Analysts, and Credit/Risk teams to serve data needs for modeling, dashboards, and compliance reports.

- Maintain documentation of data sources, table structures, and business logic.

Required Skills & Experience :

1. 3+ years of experience in a Data Engineering or Data Ops role, preferably in BFSI, f intech, or startup environments.

2. Strong hands-on experience with SQL, Python, and data pipeline frameworks

3. Exposure to MySQL/PostgreSQL, MongoDB, or NoSQL databases.

4. Experience working with API integrations, especially with credit bureaus, Aadhaar/PAN verifiers, or Alternate data sources device, 3rd party data

5. Understanding of data modeling, DPD buckets, and loan lifecycle data (LOS/LMS, collections, etc.