Manager, Data Engineering and Analytics RecologyQuest Technology Management • Sacramento, California, United States
Manager, Data Engineering and Analytics Recology
Quest Technology Management
- Sacramento, California, United States
- Sacramento, California, United States
Über
This role is hybrid, in-office three days per week and the rest can be remote.
Essential Responsibilities
Manages and coaches Data Engineers, Data Analysts, and a Product Owner, providing technical direction, prioritization, and performance feedback.
Partners with the Product Owner to define, prioritize, and maintain the data and analytics backlog.
Leads delivery using Scrum / Agile practices, including sprint planning, refinement, reviews, and retrospectives.
Balances feature delivery, platform health, and technical debt.
Remains hands‑on with architecture, development, complex data pipelines, modeling decisions, and priority engineering work.
Owns and supports a cloud‑based data environment such as Microsoft Fabric or AWS, including environment setup, deployment pipelines, monitoring, and operational support.
Establishes standards for data pipelines, semantic models, testing, and release management.
Oversees production operations, incident response, and root cause analysis.
Identifies opportunities to apply analytics and AI to improve efficiency, insight quality, and decision making.
Owns data governance practices, including data quality checks, documentation, lineage, and metric definitions.
Enforces role based access, environment segregation (Dev/UAT/Prod), and secure data access patterns.
Ensures consistency and trust across reports, dashboards, and semantic models.
Other duties as assigned.
Qualifications
10+ years of experience in data engineering, analytics engineering, or BI delivery in production environments.
High school diploma or GED required.
Bachelor’s degree preferred.
Demonstrated experience leading teams or acting as a technical lead with ownership of delivery outcomes.
Strong SQL skills with experience designing scalable ELT/ETL pipelines and data models (warehouse/lake house).
Hands on experience supporting cloud based data platforms, including monitoring and operational support.
Experience working in Scrum / Agile delivery models and collaborating closely with a Product Owner.
Experience with lake houses, warehouses, pipelines, semantic models, deployment pipelines.
Azure/AWS cloud experience (identity, security, storage, automation).
Python experience.
Experience supporting analytics or data platforms used by AI or machine learning solutions.
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Sprachkenntnisse
- English
Hinweis für Nutzer
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