Senior Data Engineer

At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.

This Position reports to:

ELSE Global Sustainability Business Proc

Your role and responsibilities:

In this role, you will lead and support enterprise-level data engineering initiatives across the Business Analytics division. You will be responsible for designing, developing, optimizing, and maintaining scalable data platforms, pipelines, and analytical datasets primarily within the Microsoft Azure and Snowflake ecosystem. You will work closely with analytics teams, business stakeholders, and cross-functional IT teams to ensure reliable, secure, and high-quality data delivery for reporting, analytics, automation, and business intelligence solutions.

The ideal candidate should possess strong expertise in modern data engineering concepts, cloud-based data warehousing, ETL/ELT development, data modeling, and large-scale data transformation. The role also requires strong collaboration skills, ownership, and the ability to support evolving analytics and reporting demands across the organization.

The work model for the role is: Hybrid

This role is contributing to the Electrification Business in Service division in Bangalore, India.

You will be mainly accountable for:

- Designing and developing end-to-end scalable ETL/ELT pipelines using Snowflake (Snowpipe, Streams, Tasks, Stored Procedures), Azure Data Factory, SQL, and related Azure services to ingest, transform, and deliver robust data models and analytics-ready datasets across data layers.

- Managing end-to-end data engineering processes including data ingestion, transformation, cleansing, validation, and integration from multiple source systems with strong data quality and governance standards.

- Supporting the complete data engineering lifecycle including development, testing, deployment, monitoring, troubleshooting, and performance optimization of production pipelines and platforms.

- Managing analytics-ready data across bronze, silver, and gold layers, supporting multiple consumption patterns including Power BI semantic models, Dataverse, direct BI integrations, and data exports with performance tuning and governance.