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.
