Job Summary

All about the role: As a Data Engineering Manager, you are a leader of builders. You are not just a people manager; you are a technical authority who has grown from the ground up in Data Engineering.

Your mission is twofold: to accelerate the professional growth of your engineers and to steer your team toward building state-of-the-art AI and data solutions that business stakeholders trust to drive revenue. You will be responsible for a high-performing organization where technical excellence and business acumen are the standard.

Key responsibilities

- People Leadership: Actively coach and mentor Data Engineers to grow their technical and leadership skills. You are responsible for the career trajectory and performance of your team.
- Technical Authority: Serve as a hands-on technical lead when necessary. You must be able to dive into code reviews, architectural discussions, and system design to ensure the team maintains a high technical bar.
- Business Alignment: Partner with business stakeholders to translate their goals into technical roadmaps. Ensure your team s output is viewed as a "Revenue Center" by delivering trusted, high-impact data products. Define and report Key Performance Indicators and launch impact as part of regular business reviews and contribute to metric-based annual quarterly objectives and key results (OKR) setting.
- Solution Strategy: Steer the team in building scalable, modern data architectures (Data Mesh/Medallion) that enable advanced AI and agentic flows.
- Operational Excellence: Own the reliability, security,



and cost-efficiency of the data platform within your domain. Drive a culture of "you build it, you run it."

The Tech stack

Our platform is built on a state-of-the-art up-to-date stack. You will oversee a landscape that leverages:
- Processing Analytics: High-scale processing via Azure Databricks , Python , and PySpark .
- Transformation Ingestion: Modern data modeling with dbt and cloud-native ingestion via Azure Data Factory (ADF) .
- Orchestration DevOps: Complex workflow management using Apache Airflow and a robust CI/CD culture centered on GitHub .

Qualifications

- Experience: Solid and progressive (several years) experience in Data Engineering, with at least 3-5 years in a leadership or management role.
- Technical Background: You must have a proven track record as a hands-on builder in cloud-based data environments (preferably Azure Databricks).
- Leadership Philosophy: Demonstrated success in developing engineering talent and building high-performing, autonomous teams.
- Communication: Ability to bridge the gap between deep technical implementation and C-suite business strategy.
- Problem Solving: Experience handling large-scale technical ambiguity and delivering solutions that directly impact company revenue.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Engineering Manager (Bengaluru)
🏢 Electrolux
📍 Bengaluru