Data Engineer (all genders)

Mettler Toledo AG; Warszawa; On-site; PLN 169,491 - 254,237; Full time

Job summary

Mettler Toledo AG in Warsaw is seeking a Data Engineer to design, build, and maintain the central data platform supporting analytics and AI/ML initiatives. You will work closely with teams to ensure high-quality data integration and delivery.

This role involves developing scalable data pipelines, implementing ETL processes, and enhancing the overall data architecture. Candidates should be knowledgeable in modern data technologies like Databricks and Snowflake.

Qualifications

• Experience in developing and maintaining ETL/ELT processes.
• Strong understanding of data quality rules and methodologies.
• Ability to collaborate with technical and non-technical stakeholders.

Responsibilities

• Design and build scalable data pipelines for diverse data types.
• Monitor and troubleshoot data flows to ensure availability.
• Automate workflows to improve efficiency and accuracy.

Skills

Data engineering

ETL/ELT processes

Data pipelines

CI/CD standards

Collaboration with cross-functional teams

Tools

Databricks

Snowflake

Orchestration tools

Job description

The Data Engineer (all genders) will design, build and maintain METTLER TOLEDO’s central data platform supporting analytics, data distribution and AI/ML initiatives. This role involves developing scalable data pipelines, ensuring high-quality and secure data flows, and contributing to the foundation that powers advanced analytics and business insights across the organization. The person on this position will work closely with data scientists, analysts, and business stakeholders to design, build, deliver and support trusted, well‑structured and secure high quality data for operational, analytical and AI/ML use cases.

Responsibilities

• Contribute to the development of the enterprise data lake/lakehouse using modern technologies (Databricks, Snowflake)
• Build and maintain data integration pipelines for batch and streaming data between internal systems, external partners and cloud services
• Implement ETL/ELT and reverse ETL processes to support analytics, reporting and AI/ML workloads
• Develop, optimize, and maintain scalable data pipelines for structured, semi structured, and unstructured data
• Monitor, troubleshoot, support and resolve any issues with data pipelines and data availability
• Automate ingestion, transformation, and distribution workflows using orchestration tools
• Create and maintain metadata catalogs, data lineage and feature stores
• Collaborate closely with cross-functional teams and business stakeholders to understand data requirements and deliver efficient technical solutions
• Evaluate and adopt new tools and technologies to improve platform performance, cost management and engineering practices
• Follow best-in-class development, testing, and documentation standards, especially also using CI/CD pipelines
• Apply and maintain data quality rules ensuring accuracy, completeness, and consistency across pipelines