Senior Data Engineering Manager
New
Y
YipitDataMarket Research, Analytics
This role may be performed fully remotely within the United States.Full-TimeManager
SalaryThe annual salary for this position is anticipated to be up to $215,000 per year, with a variable target up to 10%. The compensation package also includes equity.
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Job Details
- Experience
- 8+ years of professional experience in data engineering, data architecture, big data development, ETL engineering, or related technical roles; 3+ years of managerial experience.
- Required Skills
- SQLETLAirflowData engineeringData modelingDatabricksPySpark
Requirements
- 8+ years of professional experience in data engineering, data architecture, big data development, or related fields.
- 3+ years of managerial experience, including mentoring and leading technical teams.
- Hands-on experience in a player-coach capacity.
- Strong proficiency with SQL, PySpark, and Databricks.
- Experience with Airflow or similar workflow orchestration tools.
- Demonstrated experience building, maintaining, or scaling business-critical data systems.
- Experience working with application teams with OLTP and OLAP use cases.
- Deep technical judgment in data modeling, pipeline architecture, observability, and production reliability.
- Strong communication and cross-functional collaboration skills.
- Proficiency with AI coding tools (e.g., Claude Code, Codex, Cursor).
Responsibilities
- Lead, coach, and develop a global team of data engineers while maintaining hands-on involvement in architecture, design, and code reviews.
- Partner with Technical Product Managers and data leads to translate roadmaps and customer needs into scalable technical plans.
- Build and optimize large-scale data pipelines, data models, and QA/observability frameworks.
- Collaborate with business stakeholders across research and operations to support reliable delivery of data products and incident resolution.
- Utilize AI coding tools to accelerate engineering, improve documentation, and increase team productivity.
- Create clarity and momentum in ambiguous environments by breaking down complex data challenges into actionable engineering plans.
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