Data Engineer - Python & Snowflake

We are seeking an experienced Senior Data Engineer to join our enterprise data and analytics programme. The ideal candidate will bring strong, hands-on expertise in Python, Snowflake, SQL, and other data engineering technologies.

In this role, you will design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and data solutions that support enterprise data platforms and analytics requirements.

The position demands strong programming and database skills, proven experience with data ingestion and transformation, Snowflake development capability, and the ability to deliver high-performance, dependable data solutions.

Candidates with previous experience in the Banking and Financial Services domain will be preferred.

Key Responsibilities

1. Data Engineering & Pipeline Development

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows.
• Create Python-based solutions for data ingestion, transformation, validation, and processing.
• Develop and maintain data pipelines that bring together information from databases, APIs, files, and enterprise data sources.
• Apply business rules and perform data transformations according to functional requirements.
• Manage large datasets and ensure efficient processing performance.

2. Snowflake Development & SQL Optimization

• Develop and enhance data solutions using the Snowflake Data Warehouse.
• Write complex SQL queries with a focus on performance optimization.
• Tune Snowflake queries, data structures, and workloads to improve performance and scalability.
• Design and maintain data models that support analytical and reporting needs.
• Apply data warehousing concepts, dimensional modelling, and data marts in solution delivery.

3. Data Quality & Performance Management

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

4. Integration & Deployment

• Create data integrations using REST APIs and structured or semi-structured data formats.
• Work with JSON, CSV, and Parquet files.
• Apply Git and CI/CD practices for version control and deployment workflows.
• Participate in code reviews, testing, deployments, and production support activities.
• Adhere to 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 resolve technical issues.
• Deliver high-quality, scalable data engineering outputs.

Mandatory Skills

• 8+ years of experience in Data Engineering, preferably in 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 skills, including Joins, CTEs, Window Functions, Stored Procedures, and Query Optimization.
• Strong understanding of ETL/ELT architecture and data pipeline development.
• Experience in data ingestion, transformation, and processing of large datasets.
• Good 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, and error handling.
• Strong analytical, problem-solving, and communication skills.