What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years of data engineering or backend data infrastructure experience
- 2+ years of hands-on Databricks Spark or distributed data processing experience in production
- Strong proficiency with PySpark and Python
- Experience with data modeling
- Experience with Airflow dbt or similar orchestration and transformation tools
- Experience with data governance lineage or security best practices
- Experience with Azure AWS or Google Cloud
- Strong knowledge of CI/CD tools and version control workflows
- Experience with relational and NoSQL databases
- Experience monitoring debugging and scaling cloud-based data systems
- Strong communication skills and ability to work independently in a remote team
Nice to have
- Collaborative
- Curious
- Customer centric
- Independent
- Detail oriented
Day to day
- Design and optimize scalable data pipelines in Databricks for large-scale data processing
- Collaborate with data scientists engineers and cloud architects to build secure reliable data systems
- Automate infrastructure and support production data workflows across cloud environments