Analytics Engineer III
Tasks
- Architect observability for data and ML
- Build MLOps platform components
- Build lakehouse pipelines with Delta Lake
- Conduct code and design reviews
- Define and enforce data engineering standards
- Deploy and manage Databricks workflows
- Design ML pipelines for training and serving
- Design data products and pipelines
- Develop reusable engineering libraries and templates
- Document technical decisions and runbooks
- Ensure GxP and HIPAA data governance compliance
- Implement CI/CD for ML
- Lead cloud migration to AWS and Kubernetes
- Manage production ML pipeline schedules
- Tune Databricks performance
Perks/Benefits
- N/A
Skills/Tech-stack
ADLS | AKS | AWS | Amazon EKS | Amazon S3 | Amazon SageMaker | Apache Airflow | Asset bundles | Automated testing | AzureML | BentoML | CI/CD | DBT | DVC | Dagster | Databricks | Databricks (asset) | Databricks Asset Bundles | Databricks SQL | Delta Lake | Delta Live Tables | Delta Live) | Docker | DuckDB | Evidently | Experiment tracking | FastAPI | Feast | Feature Store | GitHub Actions | Grafana | Great Expectations | GxP | HIPAA | IAM | KServe | Kedro | Kubernetes | ML model monitoring | MLflow | Model Monitoring | Model Registry | Pandas | Pandera | Poetry | Polars | Prometheus | PySpark | Pytest | Python | RAG | Ruff | SQL | Secrets management | Structured Streaming | Triton | Unity Catalog | Vector Databases
Education
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