Purpose

We are seeking a Data Engineering Manager to lead a small, high-performing team responsible for delivering scalable, reliable, and cost-effective data staging and analytics solutions across our enterprise data ecosystem.

This role is accountable for the operational reliability, performance, and continuous improvement of enterprise data platforms that power business intelligence, reporting, and emerging advanced analytics use cases. While not an AI engineering role, the successful candidate will understand the data patterns and platform capabilities required to support machine learning and AI-driven initiatives as they arise.

You will oversee intake, estimation, prioritization, resourcing, and delivery while ensuring alignment with enterprise data architecture, governance standards, and long-term platform direction. The idóneo candidate combines strong delivery leadership with sound engineering judgment and a pragmatic approach to technology decisions.

Our environment includes Snowflake for centralized analytics aggregation,



alongside row-based platforms such as Postgres and cloud services (Azure/AWS). Success in this role requires the ability to balance these technologies effectively and deliver trusted, analytics-ready data efficiently.

Key Responsibilities
Team Leadership & Delivery
- Lead, mentor, and develop a small team of data engineers
- Establish clear delivery processes, including backlog management, sprint planning, and release coordination
- Drive predictable execution, measurable outcomes, and continuous improvement
- Define and track delivery KPIs including reliability, cycle time, defect rates, and platform stability
- Oversee operational support, incident management, and structured root cause analysis for data pipelines
Intake, Prioritization & Resourcing
- Own structured intake and estimation processes for new data initiatives
- Partner with stakeholders to prioritize work based on business value, risk, and capacity
- Manage team workload

📌 Sr Data Engineer Manager (Ciudad de México)
🏢 Nuclear Share
📍 Ciudad de México