Sr. Data Engineer
Tasks
- Build and optimize data pipelines
- Build real time streaming event driven pipelines
- Design data integrations
- Engineer lakehouse architectures
- Ensure data validation lineage and monitoring
- Establish CI CD deployment pipelines for data assets
- Implement data governance frameworks
- Implement data masking and row level security with data lineage
- Implement data models for analytics
- Implement infrastructure as code for data engineering
- Mentor junior engineers and promote Agile DataOps practices
- Optimize relational dimensional and graph data models
- Orchestrate workflows
- Support MLOps feature pipelines
- Tune Azure SQL databases stored procedures and T SQL queries
Perks/Benefits
- 401k
- Dental insurance
- Medical insurance
- Mentorship
- Onsite work
- PTO
- Paid Holidays
- Professional development
- Vision insurance
Skills/Tech-stack
Agile | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Data Lake Storage Gen2 | Azure DevOps | Azure Event | Azure Event Hubs | Azure Pipelines | Azure SQL | Azure SQL Database | Azure SQL Managed Instance | Azure Stream | Azure Stream Analytics | Azure Synapse | Azure Synapse Analytics | CI/CD | Data Factory | Data Governance | Data Lake Storage Gen2 | Data Lineage | Data Modeling | Data Monitoring | Data Validation | Data masking | Databricks | Delta Lake | Delta table | Dimensional Modeling | ELT | ETL | Event Driven | Event Hubs | Event-driven architecture | Infrastructure as Code | Lakehouse | Managed Instance | Medallion Architecture | Microsoft Fabric | Microsoft Purview | PySpark | Python | Real Time | Real-time analytics | Row Level Security | SQL Database | SQL Managed Instance | Semantic data | Semantic data modeling | Spark | Stored Procedures | Stream Analytics | Synapse Analytics | T-SQL | Unit Testing | Version control | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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