Data Engineer - Python & Snowflake

We are seeking an experienced Senior Data Engineer with hands-on expertise in Python, Snowflake, SQL, and core data engineering technologies to join our enterprise data and analytics programme.

The selected candidate will design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and data solutions that support enterprise data platforms and analytics requirements.

This role demands strong programming and database capabilities, proven experience in data ingestion and transformation, Snowflake development experience, and the ability to deliver high-performance, scalable, and dependable data solutions.

Candidates with prior experience in the Banking and Financial Services (BFSI) domain will be preferred.

Key Responsibilities

1. Data Engineering & Pipeline Development

• Design, build, and maintain robust, scalable data pipelines and ETL/ELT workflows.
• Create Python-based solutions for data ingestion, transformation, validation, and processing.
• Design data pipelines to bring together data from databases, APIs, files, and other enterprise data sources.
• Translate functional requirements into business rules and data transformations.
• Manage large datasets and ensure efficient data processing.

2. Snowflake Development & SQL Optimization

• Develop and optimize data solutions using Snowflake Data Warehouse.
• Write complex, performance-optimized SQL queries.
• Improve Snowflake query performance through optimization of queries, data structures, and workloads for scalability.
• Design and maintain data models to support analytical and reporting requirements.
• Apply data warehousing principles, dimensional modeling, and data mart development.

3. Data Quality & Performance Management

• Implement data-quality controls, reconciliation, logging, monitoring, and error handling mechanisms.
• Diagnose pipeline failures, data inconsistencies, and performance bottlenecks.
• Conduct debugging and root-cause analysis for data-related issues.
• Ensure data accuracy, reliability, and consistency across data platforms.

4. Data Integration & Deployment

• Build data integrations using REST APIs and structured or semi-structured data formats.
• Work with JSON, CSV, and Parquet file formats.
• Use Git and CI/CD practices for version control and deployment.
• Participate in code reviews, testing, deployment, and production support activities.
• Follow engineering standards and best practices to ensure secure and reliable data handling.

5. Collaboration & Production Support

• Partner with Data Architects, Business Analysts, Data Scientists, and application teams.
• Collaborate with cross-functional groups to deliver data engineering solutions.
• Provide production support and address technical issues.
• Deliver high-quality, scalable, and reliable data engineering outputs.

Mandatory Skills

• 8+ years of experience in Data Engineering, preferably within the Banking / BFSI domain.
• Strong hands-on experience in Python programming for data engineering and automation.
• Strong hands-on experience with Snowflake Data Warehouse.
• Advanced SQL knowledge, including Joins, CTEs, Window Functions, Stored Procedures, and Query Optimization.
• Good understanding of ETL/ELT architecture and data pipeline development.
• Experience in data ingestion and transformation of large datasets.
• Strong understanding of data warehousing concepts, dimensional modelling, and data marts.
• Experience integrating data from databases, REST APIs, files, and enterprise data sources.
• Hands-on experience with JSON, CSV, and Parquet formats.
• Experience with Git, version control, and CI/CD practices.
• Strong debugging, troubleshooting, and production support skills.
• Knowledge of data-quality checks, reconciliation, logging, monitoring, and error handling.
• Strong analytical, problem-solving, and communication skills.