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

The candidate will be responsible for designing, developing, and maintaining scalable data pipelines, ETL/ELT workflows, and data solutions supporting enterprise data platforms and analytics requirements.

The role requires strong programming and database skills, experience in data ingestion and transformation, Snowflake development, and the ability to build high-performance, scalable, and reliable 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, develop, and maintain robust and scalable data pipelines and ETL/ELT workflows.
- Develop Python-based solutions for data ingestion, transformation, validation, and processing.
- Build data pipelines to integrate data from databases, APIs, files, and enterprise data sources.
- Implement business rules and data transformations based on functional requirements.
- Handle large datasets and ensure efficient data processing.

2. Snowflake Development & SQL Optimization

- Develop and optimize data solutions using Snowflake Data Warehouse.
- Write complex and performance-optimized SQL queries.
- Optimize Snowflake queries, data structures, and workloads for performance and scalability.
- Design and maintain data models for analytical and reporting requirements.
- Apply data warehousing concepts, dimensional modelling, and data mart development.

3. Data Quality & Performance Management

- Implement data-quality checks, reconciliation, logging, monitoring, and error handling.
- Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.




- Perform debugging and root-cause analysis of data-related issues.
- Ensure data accuracy, reliability, and consistency across data platforms.

4. Data Integration & Deployment

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

5. Collaboration & Production Support

- Work closely with Data Architects, Business Analysts, Data Scientists, and application teams.
- Collaborate with cross-functional teams to deliver data engineering solutions.
- Provide production support and resolve technical issues.
- Ensure high-quality, scalable, and reliable data engineering deliverables.

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.
- Robust analytical, problem-solving, and communication skills.

📌 Data Engineer - Python & Snowflake (India)
🏢 Luxoft India
📍 India