We are seeking a Databricks Engineer to drive the design, development, and optimization of data pipelines and analytics solutions on the Databricks Lakehouse platform. This role is ideal for a hands-on technical leader who is passionate about big data technologies, cloud computing and enabling business insights through scalable data architectures.
Locations:
- Serbia
- Albania
- Bosnia and Herzegovina
- Montenegro
- North Macedonia
- Ukraine
- Georgia
- Argentina
- Brazil
- Estonia
- Latvia
- Lithuania
- Finland
- Romania
- Hungary
- Slovakia
- Slovenia
- Czech Republic
Requirements:
- Bachelors or Master's degree in Computer Science, Information Technology, Engineering or related field;
- 5+ years of experience in Data Engineering or Big Data roles;
- 2+ years of hands-on experience with Databricks, Spark (PySpark or Scala) and Delta Lake;
- Strong knowledge of cloud platforms (AWS, Azure or GCP) and modern data architectures (Lakehouse, Data Mesh, etc.);
- Proficiency in SQL, Python and distributed data processing;
- Experience with CI/CD, version control (Git) and DataOps in a data environment;
- Deep understanding of data governance, cataloging and security concepts;
- Experience leading a team or a project, acting as a team/tech lead of a project.
Nice to Have:
- Databricks (Pro, Architect) certification - Experience with machine learning pipelines and MLOps in Databricks;
- Exposure to streaming technologies (Kafka, Spark Structured Streaming);
- Knowledge of DBT, Airflow or other similar transformation and orchestration tools.
Other skills:
- English excellent written and verbal communication skills;
- Ability to work in a global multi-cultural and multi-national company;
- Ability to lead conversations with both technical and business representatives;
- Proven ability to work both independently and as a part of an international project team.
Job Responsibilities:
- Lead end-to-end development of data pipelines, ETL/ELT processes and batch/streaming solutions using Databricks and Apache Spark;
- Design and implement Lakehouse architectures that align with business and technical requirements;
- Collaborate with data scientists, analysts and engineers to deliver high-performance data products and ML features;
- Define and enforce coding standards, best practices and performance tuning strategies across Databricks notebooks and jobs;
- Optimize data models in Delta Lake and implement data governance standards using Unity Catalog;
- Manage integration of data sources across cloud platforms (e.g. AWS, Azure, GCP) using native and third-party connectors;