Offer summary

Qualifications:

Master’s degree in Data, Computer Science, Information Management, or a related field., 8+ years of experience in software and data engineering, with at least 4 years in Data Pipeline Engineering., Strong proficiency in Databricks and programming languages such as Python and SQL., 4+ years of experience with cloud technologies like Azure and AWS, with leadership and communication skills..

Key responsibilities:

Lead teams of data engineers to foster collaboration and innovation.

Execute data engineering strategies in partnership with stakeholders and define best practices.

Implement data pipelines and platforms while ensuring high-quality data management solutions.

Collaborate with cross-functional teams to address technical requirements and improve efficiency.

Job description

Role - Lead Data Engineer

Seniority level - Expert

Location - Warsaw (PL)

Remote - 100%

Assignment period - 01 Jul 2025 to 30 Jun 2026

Job Description:

Are you ready to lead transformative initiatives in data engineering? This position offers the opportunity to drive innovation and optimization in the development of data infrastructure and pipelines to ensure the delivery of high-quality data management solutions on a global scale.

✔️As Lead Data Engineer, the responsibilities include:

Working with teams of data engineers while fostering a culture of collaboration, innovation, and excellence.
Executing the data engineering strategy in partnership with stakeholders.
Defining and enabling the implementation of best practices, standards, tools, and services for data engineering, ensuring efficient data management.
Enabling the implementation of data pipelines, data platforms, and tools by providing engineers automation and optimization capabilities to ensure the FAIR data product creation process is efficient.
Ensuring the delivery of high-quality, scalable, and efficient data management solutions.
Collaborating with cross-functional teams to understand and address technical requirements while implementing efficiency improvements.
Providing processes and capabilities to ensure achievement of data quality and system performance measures.
Contributing to a high-performance team that fosters professional growth while promoting diversity and inclusion.

✔️Ideal candidates will have:

A Master’s degree in Data, Computer Science, Information Management, or a related field.
8+ years of experience in software and data engineering, including at least 4 years in Data Pipeline Engineering and Integration. Demonstrated experience in leading complex data engineering projects is essential.
Strong proficiency in Databricks and a deep understanding of its core functions and tools for optimizing data workflows and analytics.
Extensive experience with programming languages such as Python for data manipulation, automation, and model development.
Proficiency in SQL for complex query development, performance tuning, and data extraction across varied databases.
Hands-on experience with DevOps and CI/CD processes and tools for smooth and reliable software delivery and code deployments.
Expertise in data modelling, data integration, metadata management, and data governance to establish robust and scalable data architectures.
4+ years of strong experience with cloud technologies such as Azure and AWS (certifications are a plus).
Familiarity with life sciences regulatory requirements and standards.
Experience in designing scalable data engineering solutions, working closely with business teams, and leading virtual technical teams.
Proven leadership abilities, exceptional communication skills, and adept stakeholder management to guide virtual technical teams and drive cross-functional initiatives.