Senior Databricks Engineer
Tasks
- Apply data warehousing dimensional modeling
- Automate Databricks deployments with CI CD
- Build PySpark and SQL ETL ELT jobs
- Conduct code reviews and mentor engineers
- Deploy Databricks data pipelines
- Design scalable data pipelines
- Develop Databricks Delta Live Tables pipelines
- Develop data infrastructure
- Develop native Databricks dashboards
- Develop reusable Python libraries
- Establish data quality standards
- Implement Slowly Changing Dimensions
- Implement medallion architecture
- Implement structured streaming pipelines
- Integrate data ingestion from REST APIs
- Manage infrastructure as code
- Monitor data quality dashboards
- Share data with external BI tools
- Tune Spark jobs and Databricks clusters
Perks/Benefits
- 401k matching
- Dental insurance
- Flexible spending accounts
- Health insurance
- Paid Holidays
- Paid time off
- Remote work
- Vision insurance
Skills/Tech-stack
Asset bundles | Azure Data | Azure Data Lake | Azure Data Lake Storage | Azure Data Lake Storage Gen2 | Azure DevOps | Azure Key Vault | CI/CD | Data Lake Storage Gen2 | Data Quality | Data Vault | Data Vault 2.0 | Data Warehousing | Data quality monitoring | Databricks | Databricks (asset) | Databricks Asset Bundles | Databricks Delta | Databricks Delta Live Tables | Delta Lake | Delta Live Tables | Dimensional Modeling | Elasticsearch | Git | HTTP | Infrastructure as Code | Jupyter Notebooks | Key Vault | Lucene | Medallion Architecture | Oracle PL | Oracle PL/SQL | PL/SQL | PeopleSoft | Power BI | PySpark | Python | Quality monitoring | REST APIs | SAP BusinessObjects | SQL | Slowly Changing Dimensions | Solr | Structured Streaming | Tableau | “as-code”
Education
N/A
Roles
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