Senior Databricks Data Engineer
Summary
Senior Databricks Data Engineer designing data pipelines and large-scale data processing solutions on Databricks and cloud platforms (AWS, Azure, GCP) with Python, for a technology client via Optiveum. 100% remote within Poland on a B2B contract paying up to 38 EUR/hour + VAT.
Senior Databricks Data Engineer
Location: 100% Remote (Poland)
Rate: up to 38 EUR + VAT (B2B) Work model: B2B Contract Contracting Party: Optiveum
Optiveum is currently looking for a Senior Databricks Data Engineer to join the team of our client—a thriving technology organization with over 400 professionals dedicated to delivering advanced, data-driven solutions.
In this role, you will be part of a team whose expertise lies in Cloud & Big Data engineering. You will help build scalable architectures for processing large and complex datasets across AWS, Azure, and GCP while leveraging modern data frameworks, programming methodologies, and DevOps best practices.
Please note: Optiveum acts as the recruitment partner and the direct contracting party for this position.
Your Tasks:
Designing and implementing data processing solutions using Databricks for large-scale and diverse datasets.
Designing, building, and enhancing data pipelines with Python and cloud-native tools.
Working closely with solution architects to define and uphold best practices in data engineering.
Ensuring data consistency, security, and scalability within cloud-based environments.
Your Profile:
Solid commercial experience in data engineering, coupled with hands-on Databricks expertise.
Strong proficiency in Python for automation and data transformation.
Commercial experience working with at least one major cloud platform (AWS, Azure, or GCP).
Strong communication skills.
Advanced command of both English and Polish.
Nice-to-Have:
Solid understanding of SQL, including experience in query optimization and data modeling.
Familiarity with DevOps methodologies, CI/CD pipelines, and Infrastructure as Code (Terraform, Bicep).
Experience with real-time data streaming technologies such as Kafka or Spark Streaming.
Knowledge of cloud storage solutions like Data Lake, Snowflake, or Synapse.
Hands-on experience with PySpark for distributed data processing.
Relevant industry certifications (e.g., Databricks Certified Data Engineer Associate or cloud-based data certifications).