About the Position

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

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.
Contribute to and lead technical reviews, architecture sessions, and mentoring of less experienced engineers.
Automate infrastructure deployment with tools like Terraform, Databricks CLI, or others.
Ensure data platform solutions are secure, compliant, and scalable across global business units.

Requirements

Bachelor's 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.

We Offer

Competitive salary.
100% remote opportunity.
Flexible work environment (in-office, remote, or hybrid depending on preferences and manager approval).
Opportunities for professional growth and career advancement.
Collaborative and innovative work environment.
Paid time off, including holidays, vacation, and sick leave.
Benefits may vary by location and will be confirmed during the interview process.

Job ID

JR-124399

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Databricks Engineer

Job description