Sr. Manager, Data Engineering
New
J
JobgetherSecurity & IT
Based in United StatesFull-TimeManager
SalaryTargeted starting base salary of $135,000–$185,000 USD.
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Job Details
- Experience
- 3+ years of experience leading or managing data engineering teams, combined with 5+ years of hands-on data engineering experience
- Required Skills
- PythonSQLApache AirflowArtificial IntelligenceGCPCI/CDData modelingBigQuerydbt
Requirements
- 3+ years of experience leading or managing data engineering teams.
- 5+ years of hands-on data engineering experience in cloud environments.
- Deep hands-on experience with GCP technologies, specifically BigQuery, Cloud Composer/Apache Airflow, dbt, Python, and SQL.
- Working knowledge of Dataflow, Pub/Sub, Cloud Storage, Looker, and Cloud IAM.
- Expert-level knowledge of data modeling and architecture frameworks.
- Strong project execution, delivery management, and stakeholder management skills.
- Demonstrated hands-on use of AI tools like Copilot, Claude, or ChatGPT in engineering workflows.
- Experience driving AI adoption among engineering teams.
- Experience building foundational data platforms and capabilities.
- Strong technical accountability with a focus on code quality and production readiness.
Responsibilities
- Lead, mentor, and develop a growing global team of data engineers.
- Own team planning, estimation, prioritization, delivery tracking, and roadmap planning.
- Establish engineering and architecture standards covering code quality, testing, security, and maintainability.
- Design, build, and oversee scalable data pipelines using GCP, BigQuery, Python, SQL, dbt, and Apache Airflow.
- Drive AI adoption across engineering workflows, ensuring appropriate human review and testing.
- Build reliable, well-modeled, and AI-ready data assets for analytical and machine learning systems.
- Define and manage SLAs for data freshness, completeness, and accuracy.
- Mature CI/CD, environment management, and release processes for data and analytics code.
- Partner with data governance teams to ensure data products are documented and secure.
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