Sr. Data Engineer I
Skills
- Databricks
- PySpark ETL/ELT
- Advanced Python
- Advanced SQL and query optimization
- Cloud data services (S3, Redshift, BigQuery)
- ML tooling (MLflow, SageMaker, Databricks ML, Kubeflow)
- CI/CD for data and ML
- Containerization (Docker) and cloud deployment/orchestration
- RESTful API development and debugging
- Data modeling and data quality / MDM
Responsibilities
- Design and build scalable data extracts, integrations, transformations, and data models
- Deploy and provision data solutions across environments with automation and governance
- Define and implement data architectures optimized for speed, quality, and operational efficiency
- Collaborate with stakeholders to gather requirements and translate them into technical designs
- Develop domain expertise in enterprise datasets and drive data quality improvements
- Design, build, and maintain reproducible ML pipelines including feature engineering, training, validation, deployment, and monitoring
- Implement CI/CD for data and ML workflows, including automated testing and release automation
- Build and operate ML infrastructure: feature stores, model registries, data versioning, and experiment tracking
- Implement model governance: performance monitoring, drift detection, logging, observability, and alerting
- Support batch, streaming, and real-time inference pipelines and ensure operational reliability
- Mentor junior engineers and participate in technical design reviews
Education
- Bachelor's degree in Computer Science, Information Systems, Engineering, or related technical field
- Master's degree preferred (Computer Science, Data Science, or equivalent)
Benefits
- Medical, dental, and vision insurance
- 401(k) plan
- Paid time off, paid sick leave, and paid holidays
- Eligibility for RSUs and annual performance bonuses
- Global employee benefits offerings depending on location
Average salary estimate
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