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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
- Bachelor’s degree or equivalent in a related field
- 5+ years of experience in data engineering platform engineering or ML engineering
- Experience with major cloud data platforms and tools such as AWS GCP dbt Airflow Airbyte Redshift or BigQuery
Nice to have
- Collaborative mindset
- Dependable execution
- Humility
- Curiosity
- Openness to experimentation
Day to day
- Design and maintain scalable data systems for ingestion transformation and storage with strong testing and observability practices.
- Build automation and tooling that safely increases development velocity and supports reliable analytics and ML workflows.
- Partner with data scientists analysts and product managers to develop end-to-end AI and ML pipelines and production integrations.
Hiring process
- Complete the application
- Answer optional EEOC questions