Senior Data Engineer, Databricks
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Job Description
Senior Databricks Data Engineer building scalable data pipelines with Python and Databricks. Delivering cloud solutions across AWS, Azure, or GCP for Optiveum’s clients.
Responsibilities:
- Design and implement data processing solutions using Databricks for large-scale and diverse datasets
- Design, build, and enhance data pipelines using Python and cloud-native tools
- Collaborate closely with solution architects to define and uphold data engineering best practices
- Ensure data consistency, security, and scalability within cloud-based environments
- Work across the entire Software Development Life Cycle (SDLC)
- Leverage modern data frameworks, programming methodologies, and DevOps best practices to create efficient solutions
Requirements:
- Commercial experience in data engineering
- Hands-on Databricks expertise
- Strong programming skills in Python for automation and data transformation
- Experience with at least one major cloud platform: AWS, Azure, or GCP
- Strong communication skills
- Proficiency in English
- Nice to have: solid understanding of SQL, including query optimization and data modeling
- Nice to have: familiarity with DevOps methodologies, CI/CD pipelines, and Infrastructure as Code (Terraform, Bicep)
- Nice to have: experience with real-time data streaming technologies such as Kafka or Spark Streaming
- Nice to have: knowledge of cloud storage solutions such as Data Lake, Snowflake, or Synapse
- Nice to have: hands-on experience with PySpark for distributed data processing
- Nice to have: relevant certifications such as Databricks Certified Data Engineer Associate or cloud-based data certifications
Benefits:
- Fully remote work
- B2B cooperation contract
- Project-based or permanent job opportunities through Optiveum
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