Senior Data Engineer
Tasks
- Administer Azure databases including performance tuning backup and recovery
- Apply data masking and encryption at rest and in transit
- Assemble large complex datasets
- Backfill as technical lead for business intelligence data management
- Build ETL and ELT data pipelines
- Build enterprise data warehouse and reporting pipelines
- Design and build data models for structured and unstructured data
- Design data lake and delta lake ingestion and storage
- Develop analytics technologies for business insights
- Implement data processing pipelines
- Manage BI and data management team until replacement
- Manage cloud data hub infrastructure for data management systems
- Monitor access audit logs and enforce security
- Validate data quality using testing methodologies
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | Azure | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Databricks | Azure Event | Azure Event Hubs | Azure Stream | Azure Stream Analytics | Azure Synapse | Azure Synapse Analytics | Backup and Recovery | C++ | Cause analysis | Data Factory | Data Lake Storage | Data Management | Data Modeling | Data Pipelines | Data Quality | Data Warehousing | Data masking | Database performance | Database performance tuning | Databricks Delta | Databricks Delta Lake | Delta Lake | ELT | ETL | Encryption | Event Hubs | Hadoop | Java | Kafka | Master Data | Master Data Management | Message queuing | Metadata Management | NoSQL | Performance Tuning | Power BI | Python | Reference Data | Reference Data Management | Root Cause Analysis | Root cause | SQL | Scala | Storm | Stream Analytics | Stream processing | Synapse Analytics
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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