Data Engineering Expert for Automated Underwriting
9 hours ago
We are seeking a skilled and experienced Data Engineer to join our team at Easy Home Finance Limited. As an expert in data engineering, you will be responsible for designing and maintaining data pipelines, optimizing databases, and ensuring reliable, clean, and well-structured data to support our AI/ML models and business logic.
Key Responsibilities:
- Data Pipeline Development:
Design, develop, and maintain ETL pipelines to ingest, transform, and load data from multiple sources (e.g., MySQL, MongoDB, Elastic) into a centralized data store for model training and inference.
Implement workflows using tools like Apache Airflow, AWS Glue, or equivalent to ensure timely and reliable data availability.
- Data Pre-processing & Feature Engineering:
Clean, normalize, and enrich large datasets of home loan applications, both structured (e.g., financial data) and unstructured (e.g., customer narratives, supporting documents).
Collaborate with Data Scientists and ML Engineers to define and implement feature extraction, data transformations, and schema optimizations to support LLM-based underwriting models.
- Database Management & Optimization:
Work closely with the Database Administrator to configure and optimize MySQL and MongoDB for high-performance query execution and efficient data retrieval.
Ensure data integrity, consistency, and compliance with relevant security and privacy regulations.
- Infrastructure & Scalability:
Implement scalable data storage solutions on AWS (e.g., S3, Redshift, DynamoDB) and integrate these resources seamlessly with model training environments (e.g., Sage Maker).
Monitor and troubleshoot data pipelines, ensuring minimal downtime and prompt resolution of data quality issues.
- Collaboration & Best Practices:
Collaborate with Machine Learning Engineers, Data Scientists, and Backend Developers to understand data requirements and deliver solutions aligned with project goals.
Follow best practices in version control (Git), documentation, and testing to maintain a robust and reliable data infrastructure.
- Continuous Improvement:
Stay updated with the latest tools, technologies, and best practices in data engineering and cloud services.
Propose and implement improvements to enhance data quality, reduce latency, and streamline data operations.
Requirements & QualificationsWe are looking for a highly motivated and detail-oriented Data Engineer with:
- Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
The ideal candidate should have:
- At least 3 years of experience in data engineering or a related role.
A strong proficiency in SQL and experience with relational databases (MySQL) and NoSQL databases (MongoDB) is required.
- Hands-on experience with ETL/ELT frameworks and data workflow orchestration tools (e.g., Airflow, AWS Glue).
Proficiency in Python or a similar programming language for data processing is necessary.
- Familiarity with AWS cloud services (e.g., EC2, S3, Redshift, Lambda, Sage Maker) and containerization (Docker).
An understanding of data modelling, data warehousing, and schema design best practices is also essential.
The salary range for this position is approximately ₹15,00,000 - ₹25,00,000 per annum, depending on qualifications and experience.
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