Senior Data Engineer
Tasks
- Architect scalable data architectures and implementations
- Build automated ETL and ELT pipelines
- Collaborate on security access control auditing and governance
- Define data engineering standards and reusable patterns
- Design data models schemas data contracts and medallion patterns
- Develop batch and streaming data capabilities
- Establish CI CD testing monitoring and operational practices
- Implement data quality lineage metadata observability and governance
- Lead design and evolution of Databricks lakehouse pipelines
- Lead design reviews and resolve production issues
- Mentor engineers and communicate architecture decisions
- Optimize Databricks and Spark workload performance and cost
Perks/Benefits
- 401k with employer match
- Federal holidays off
- Flexible PTO
- Flexible spending account
- Health, dental, and vision insurance
- Paid Cloud Developer Accounts
- Professional development
Skills/Tech-stack
AWS | Access Control | Airflow | Amazon Kinesis | Apache Kafka | Apache Spark | Asset bundles | Auditing | Automated testing | Azure | CI/CD | Data Contracts | Data Lineage | Data Modeling | Data Quality | Data Security | Databricks | Databricks (asset) | Databricks Asset Bundles | Delta Lake | ELT | ETL | Google Cloud | Governance | Infrastructure as Code | Kafka | Lakehouse | MLflow | Medallion Architecture | Metadata Management | Observability | Privacy | Pulsar | PySpark | Python | SQL | Schema | Source Control | Spark Structured Streaming | Streaming | Structured Streaming | Terraform | Unity Catalog | “as-code”
Education
Roles
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