Data Platform Engineer

Overview

Data Engineer on the Electrolux Global Data & AI team, building and operating reliable data pipelines and trusted data products on an Azure Databricks Lakehouse, with a Data Mesh approach to domain ownership.

What you'll do

• Design and build pipelines that move data from relational databases, external sources and operational datastores into the Lakehouse, merging disparate sources into a single trustworthy picture.
• Build and maintain ELT pipelines using dbt to create clean, well-modeled, business-ready assets, applying dimensional modeling and consistent KPI definitions.
• Operate and extend the Azure Databricks Lakehouse, contributing to schema design, query optimization and scalable data processing.
• Own end-to-end pipeline orchestration in Airflow, with automatic recovery, monitoring, alerting and audit trails.
• Implement automated data quality checks and testing to continuously verify accuracy, completeness and timeliness.
• Apply data mesh principles to design data products with clear ownership, discoverability and contracts across domains.
• Bring a software engineering mindset to data engineering, using version-controlled code, CI/CD, code review and Infrastructure as Code.
• Work with business stakeholders to translate ambiguous requirements into scalable data solutions, and collaborate with the Platform and AI teams on shared infrastructure, standards and roadmap.
• Monitor and optimize computing and storage costs on Azure.
• Use AI pair-programming tools such as GitHub Copilot and build agentic CI/CD workflows in GitHub Actions.

What you'll need

• 3+ years of experience as a Data Engineer building and operating production data pipelines at scale.
• Strong hands-on skills in SQL (query optimization, schema design) and Python for pipeline development and automation.
• Practical experience with a cloud data platform (Azure strongly preferred) and modern Lakehouse or data warehouse architecture.
• Experience building ELT/ETL pipelines, ideally with dbt, and orchestrating them with a workflow manager such as Airflow.
• A track record of taking ambiguous problems from first principles to a working, reliable solution, and comfort moving across ingestion, modeling and delivery.
• Ability to explain technical trade-offs to non-technical stakeholders and translate business requirements into scalable, well-modeled data assets.
• Hands-on experience using GitHub Copilot or similar AI coding assistants in daily development, and building CI/CD pipelines in GitHub Actions.

Details

• Full-time position based in Bangalore, India.