Data Engineering Manager

Data Engineering Manager

Electrolux

Stockholm, Sweden

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 modern 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.