City:
SacramentoLocation:
1074 - Recology Service Center - Sacramento officeSubsidiary Name:
Recology Service CenterRoleThe Manager, Data Engineering and Analytics leads and actively contributes to the delivery of enterprise data analytics. This is a hands-on role that is responsible for managing Data Engineers, Data Analysts and a Product Owner while owning the design, development, and upkeep of data management solutions and reporting methodology. Drives innovative initiatives to transform data interpretation and utilization, setting standards for data-driven decision-making and empowers the team with actionable insights.
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.
