Senior Manager Data Engineering
The Senior Manager will lead and grow data engineering teams to deliver enterprise‑scale data platforms and products across finance, supply chain, R&D and operations. The role focuses on modernizing the enterprise data fabric, building scalable pipelines and enabling advanced analytics and AI initiatives.
Skills required
About this role
Career Category
EngineeringJob Description
Senior Manager – Data Engineering (EDSE)
About the Role
Let's do this. Let's change the world.
We are looking for an experienced Senior Manager, Data Engineering to lead strategic data engineering initiatives within Enterprise Data Strategy & Engineering (EDSE). This role will guide high-performing engineering teams, deliver enterprise-scale data platforms and data products, modernize the Enterprise Data Fabric (EDF), and enable advanced analytics, AI, and digital transformation across Finance, Supply Chain, Research & Development, Operations, and other business domains.
Key Responsibilities
Strategic Leadership
- Lead and develop data engineering teams responsible for enterprise data products, platforms, and mission-critical data solutions.
- Define and execute the domain data engineering roadmap in alignment with EDSE and enterprise priorities.
- Advance modern data engineering, cloud, AI, automation, and observability capabilities.
- Collaborate with business stakeholders, product teams, architecture, and platform engineering groups to deliver measurable business outcomes.
Delivery & Execution
- Oversee the design, development, deployment, and support of scalable data products and pipelines.
- Ensure strong delivery across build, enhancement, RunOps, and KTLO activities.
- Manage commitments, capacity, priorities, risks, and vendor execution.
- Set engineering standards, quality practices, and performance measures across the team.
Enterprise Data Platform & Architecture
- Lead implementation of the Enterprise Data Fabric (EDF), semantic layer, data products, and governance initiatives.
- Work with Enterprise Data Architecture and Platform Engineering teams to deliver scalable, secure, and reusable solutions.
- Promote metadata-driven engineering, automation, observability, data quality, and governance practices.
AI & Innovation
- Champion AI, traditional ML, Generative AI, Agentic AI, and automation to improve engineering efficiency and business value.
- Assess and adopt emerging technologies that accelerate delivery, improve data accessibility, and strengthen platform reliability.
- Drive innovation through reusable accelerators, engineering frameworks, and platform modernization.
People Leadership
- Build, mentor, and develop high-performing data engineering teams.
- Create a culture of technical excellence, collaboration, innovation, and continuous learning.
- Oversee performance management, career development, succession planning, and talent acquisition.
- Lead global, multi-vendor delivery teams aligned to organizational goals.
Required Qualifications
- 12+ years of experience in data engineering, data platforms, analytics engineering, or related fields.
- 5+ years of leadership experience managing engineering teams and large-scale delivery programs.
- Strong experience with Databricks, Spark, PySpark, SQL, Python, AWS, and cloud-native data architectures.
- Proven ability to build enterprise-scale data platforms, data products, and integration solutions.
- Strong understanding of Data Fabric, Data Mesh, Lakehouse, metadata management, and governance.
- Experience working in Agile or SAFe delivery environments.
- Excellent communication, stakeholder management, and leadership capabilities.
