Data Platform Lead

10 hours ago


Stockholm, Stockholm, Sweden Rillion AB Full time
About Us
Rillion AB is a global company with 30 years' experience in the AP Automation industry. We specialize in digitalizing and automating the entire invoice handling process, enabling finance teams to save time and effort while reducing the possibility of human error.

We believe that diversity is integral to our success and do not discriminate based on race, color, religion, age, or any other basis protected by law.

Job Description
We are looking for an experienced Engineering Manager to lead and grow our data team, driving the development of a modern, scalable data platform. In this role, you'll combine technical leadership with hands-on data engineering, ensuring that our data infrastructure supports business and product goals.

You'll work closely with data engineers, software developers, product managers, and business stakeholders to create a data-driven foundation for decision-making and product innovation. If you're an experienced leader with a strong data engineering background who thrives in a collaborative and fast-moving environment, we'd love to hear from you.

Responsibilities
- Lead and mentor a team of data engineers, fostering a strong engineering culture.
- Own the data platform, ensuring scalability, security, and performance.
- Collaborate across teams, working closely with AI, product, and business teams to enable data-driven insights.
- Drive architectural decisions for data pipelines, storage, and processing.
- Ensure high-quality data by implementing best practices in governance, monitoring, and data integrity.

What You'll Bring
- Experience leading data engineering or data platform teams in a product-driven company.
- Hands-on experience with Python, SQL, and cloud-based data stack (Databricks, BigQuery or similar).
- Proven ability to design and scale data pipelines, ETL processes, and analytics solutions.
- Strong collaboration and stakeholder management skills.
- Fluency in English.

Bonus Points
- Experience with BI tools (Power BI), real-time data processing, or MLOps.
- Experience from product organizations.

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