Data Engineer
Tasks
- Build and operate batch and streaming data pipelines
- Build automated ETL/ELT pipelines
- Collaborate to deliver reusable data products
- Design develop maintain Databricks based data pipelines
- Design maintain data models schemas tables and medallion architecture
- Develop production data processing solutions
- Document data models and pipeline designs
- Implement data protection access control auditing and governance
- Implement data quality checks automated testing monitoring lineage and metadata management
- Manage Databricks notebooks jobs workflows clusters and compute
- Optimize Spark workloads and Databricks resources
- Support Databricks deployments with CI CD infrastructure as code and source control
- Support data discovery governance and access controls with Unity Catalog
- Troubleshoot Databricks workloads data pipelines storage and production data services
Perks/Benefits
- 401k employer match
- Federal holidays off
- Flexible PTO
- Flexible spending account
- Health, dental, and vision insurance
- Life insurance
- Long-term disability
- Paid Cloud Developer Accounts
- Professional development
- Referral bonuses
- Short-term disability
Skills/Tech-stack
AWS | Airflow | Apache Spark | Azure | CI/CD | Data Governance | Data Lineage | Data Modeling | Data Quality | Data Security | Databricks | Delta Lake | Docker | Docker Compose | ELT | ETL | Google Cloud | Infrastructure as Code | Kafka | Kinesis | Kubernetes | Lakehouse Architecture | Metadata Management | Monitoring | PySpark | Python | SQL | Source Control | Spark Structured Streaming | Structured Streaming | Unity Catalog | “as-code”
Education
Roles
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