We're seeing an experienced Senior Data Engineering Manager who thrives on empowering teams, driving data excellence, en enabling data-driven decision-making across an organization. This leader will directly manage a team of skilled data engineers, fostering a collaborative and innovative environment focused on delivering scalable, reliable, and high-quality data solutions.

• You'll directly manage a team of data engineers, providing guidance, mentorship, and fostering a culture of continuous learning and technical excellence.
• You'll collaborate closely with BI engineering and data platform teams to deliver scalable and reliable data solutions.
• You'll lead initiatives to improve data accessibility, ensuring data is easy to understand and actionable for business stakeholders.
• You'll develop and execute plans to enhance data quality, security, and governance, aligning with business needs and regulatory requirements.
• You'll partner with engineering, product, and business teams to define and prioritize projects that enable data-driven decision-making.
• You'll drive efforts to make data a strategic asset for the company, enabling critical decision-making capabilities for 2025 and beyond.

• Have a strong technical background in data engineering with a track record of making and guiding technical decisions.
• Bring hands-on expertise in data architecture, ETL processes, and designing scalable data pipelines.
• Are proficient in modern data stack tools and technologies, including cloud platforms (AWS, GCP, Azure), data lakes, and data warehouses like Snowflake or BigQuery.
• Balance strategic vision with the ability to dive into hands-on work when needed.
• Excel in verbal and written communication, effectively explaining complex technical concepts to both technical and non-technical audiences.
• Are skilled at leading teams, including those with highly senior individual contributors.
• Have experience mentoring data engineers and helping them enhance their technical skills and decision-making abilities.
• Possess experience with distributed systems and large-scale data processing frameworks such as Spark or Flink.
• Are available to work also in the US timezone (PL evenings).

• Previous experience working in fast-paced, enterprise-level environments with cross-functional teams. 
• Knowledge of machine learning pipelines or integrating analytics/BI tools into data workflows.