Databricks Data Engineer
Tasks
- Apply Databricks best practices for notebooks jobs and workflows
- Build ETL and ELT workloads
- Collaborate to translate requirements into data products
- Create curated data models
- Design scalable data pipelines
- Develop ingestion from relational databases files APIs and streaming
- Develop lakehouse architectures
- Implement Delta Lake patterns
- Implement data quality validation reconciliation monitoring
- Optimize spark jobs for performance
- Support platform standards code reviews documentation and governance
Perks/Benefits
- Employee assistance program
- Flexible work schedule
- Flexible working arrangements
- Friday afternoon off
- Hybrid work
- Life insurance
- Maternity gifts
- New baby gifts
- Paid paternity leave
- Paid sick leave
- Private medical insurance
- Provident fund
- Wedding gifts
- Yearly wellbeing days off
Skills/Tech-stack
ACID | Access Management | Apache Spark | Azure Storage | CSV | Data Modeling | Data Quality | Data Validation | Databricks | Delta Lake | ELT | ETL | Error Handling | Fact Dimension Model | Fact/Dimension | Identity and Access Management | Identity and access | JSON | Logging | Monitoring | Near-real-time | Parquet | Partitioning | PySpark | Real Time | SQL | Scala | Schema evolution | Slowly Changing Dimensions | Star Schema | Streaming | Time Travel | Unity Catalog | XML
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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