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Sr. Data Engineer
Skills
Computer ScienceAnalytical SkillsArtificial IntelligenceDashboardsData EngineeringData ScienceEngineering
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Proficiency in SQL and Python
- Strong familiarity with modern data engineering frameworks infrastructure and tooling
- Experience with data ops best practices monitoring pipeline automation and CI/CD
- Knowledge of Spark TensorFlow PyTorch or scikit-learn
- Ability to build production APIs and services including MCP servers
- Collaborative mindset dependable execution and willingness to learn
- Comfort using AI tools in daily workflows
- Bachelor’s degree or equivalent in a related field
- 5+ years of experience in data engineering platform engineering or ML engineering
- Experience with cloud data platforms and tools such as AWS GCP dbt Airflow Airbyte Redshift or BigQuery
Nice to have
- Healthcare experience
- Behavioral health experience
- EHR systems experience
- Regulated industries experience
- Curiosity
- Openness to experimentation
Day to day
- Design and maintain scalable data systems for ingestion transformation and storage with strong testing and observability
- Build automation tooling and frameworks that safely accelerate development and improve data platform reliability
- Develop end-to-end AI and ML workflows from source ingestion through productionization and downstream integration
- Support model operations with monitoring for accuracy drift bias fairness and reproducibility while collaborating across teams
Hiring process
- Complete the online application
- Answer optional EEOC questions