Data Engineer

Overview

The Data Engineer will join Agile Feature Teams delivering data products, regulatory reporting solutions, modern data platforms, and analytics capabilities. The role focuses on designing, developing, and enhancing scalable data pipelines, integrating enterprise data sources, supporting cloud data platforms, and delivering high-quality data solutions.

What you'll do

• Design, develop, and maintain scalable data pipelines and ETL/ELT solutions.
• Build data ingestion, transformation, and integration frameworks across multiple source systems.
• Develop reusable and high-performance data models, datasets, and APIs.
• Support modernization, migration, and cloud transformation initiatives.
• Work within Agile Scrum teams to deliver features aligned to business priorities.
• Participate in sprint planning, backlog refinement, estimation, and reviews.
• Collaborate with Product Owners and Business Analysts to translate requirements into technical solutions.
• Deliver features that meet functional, non-functional, and regulatory requirements.
• Build and optimize data warehouse, lakehouse, and reporting solutions.
• Develop solutions using Azure Data Services, Databricks, and modern cloud technologies.
• Ensure scalability, reliability, and performance of data platforms.
• Support data architecture standards and engineering best practices.
• Implement data quality checks, reconciliation controls, and validation frameworks.
• Ensure compliance with data governance, lineage, security, and regulatory requirements.
• Support audit readiness and control frameworks.
• Develop unit, system, and integration testing components.
• Participate in release planning and deployment activities.
• Support defect resolution and production readiness activities.
• Collaborate with BAU teams during transition and hypercare phases.
• Automate development, testing, and deployment processes.
• Improve engineering standards, reusable assets, and delivery efficiency.
• Contribute to platform modernization and innovation initiatives.

What you'll need

• 4-8 years of experience in Data Engineering or Data Platform Development.
• Strong SQL, Python, and ETL development expertise.
• Experience delivering enterprise data and analytics solutions.
• Hands-on experience with Azure Data Platform services.
• Strong problem-solving and stakeholder management skills.
• Experience working in Agile delivery teams.
• Data engineering experience with SQL Server, Oracle, PostgreSQL, Snowflake, and Databricks.
• Experience with data warehousing and data modelling.
• Experience with data lakehouse architecture.
• Experience with ETL / integration.
• Experience with Azure Data Factory (ADF).
• Experience with SSIS / Informatica.
• Experience with Apache Airflow.
• Experience with API integration.
• Experience with event-driven data processing.
• Experience with Microsoft Azure, Azure Synapse Analytics, Azure Storage, Azure Data Lake, and Azure DevOps.
• Experience with PySpark, Spark, and Git version control.
• Knowledge of data governance, data quality frameworks, data lineage, metadata management, and regulatory reporting controls.

Nice to have

• Banking or Financial Services experience.
• Regulatory reporting or risk data experience.
• Databricks and Snowflake experience.
• CI/CD and DevOps practices.
• Knowledge of modern data architecture patterns.

Details

• Location: India.
• Hybrid working.