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Global Engineering and Delivery @ DHL Supply Chain
As Global Lead – Engineering & Delivery for Intelligent Process Automation (IPA), I provide strategic and technical leadership for the design, governance, and global rollout of Intelligent Automation solutions across DHL Supply Chain. I lead a globally distributed engineering and delivery team of developers, leads, and architects, driving a modular, scalable automation strategy that enables solutions to be designed once and scaled across multiple domains and regions. My team is responsible for defining enterprise-level architecture standards, reusable frameworks, and platform roadmaps that accelerate adoption while ensuring consistency, resilience, and cost efficiency across global operations. My role spans end-to-end ownership of IPA delivery and operations, partnering with senior IT, business, and vendor leaders to govern build-and-run engagements, align automation initiatives with business priorities, and ensure delivery within agreed cost, risk, and time parameters. I actively shape the long-term automation vision, strengthening platform maturity through reusable assets, standardized components, and capability development across teams. I collaborate closely with Enterprise Architecture, Agile, and DevOps leadership to embed best practices and enable enterprise-scale execution. I continuously evaluate emerging technologies and vendor ecosystems, steering roadmap decisions and PoCs to ensure sustained relevance, scalability, and measurable business impact from the automation portfolio.
Indian Institute of Technology, Delhi
Post Graduate Diploma in Data Science & Machine Learning, Information Technology
January 1, 2023 – January 1, 2024
KLN College of Engineering, Madurai, India
Bachelor of Information Technology, Information Technology
August 1, 2007 – April 1, 2011
DHL Supply Chain
Global Lead Engineering and Delivery - Digital Transformation Office
May 1, 2023 – Present
Global · Remote
DHL Supply Chain
Global Delivery Lead - Intelligent Process Automation CoE
July 1, 2021 – May 1, 2023
Global · Remote
Wells Fargo
Corporate AVP - Robotic Process Automation
October 1, 2020 – July 1, 2021
India · Remote
ICON plc
Solution Architect - Automations
March 1, 2019 – October 1, 2020
Chennai, Tamil Nadu, India · On-site
Cognizant
Lead - Application Development
December 1, 2014 – March 1, 2019
Chennai, Tamil Nadu, India · On-site
Computer Sciences Corporation (CSC)
Programmer Analyst
September 1, 2011 – November 1, 2014
On-site
Certified ScrumMaster (CSM)
Scrum Alliance
June 25, 2026 – Present
Python for Data Science and AI - IBM Watson Studio
IBM
June 25, 2026 – Present
Intelligent Process Automation Course
Cognizant
June 25, 2026 – Present
Program Management for IT Professionals
June 25, 2026 – Present
Advanced Robotic Process Automation Developer from UiPath
UiPath
June 25, 2026 – Present
Chatbot Building Essentials - IBM Watson Assistant
IBM
June 25, 2026 – Present
UiPath Solution Architect
UiPath
June 25, 2026 – Present
Project Management Professional (PMP)
Project Management Institute
June 25, 2026 – Present
Introduction to Artificial Intelligence(AI) - IBM Watson
IBM
June 25, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows adaptability across different companies (CSC, Cognizant, ICON plc, Wells Fargo, DHL Supply Chain) and a recent pivot towards Data Science & Machine Learning, indicating a growth mindset. However, the target role is 'Frontend Developer', which is a significant shift from their recent extensive experience in RPA, AI, and project/program management. This misalignment suggests a potential cultural fit challenge for a pure frontend development role, despite a broad technical background.
Soft Skills & Operational Fit
The candidate's experience in global lead and delivery roles suggests strong leadership, project management, and potentially good communication skills. Certifications like CSM and PMP further support an operational fit for structured project environments. However, specific soft skill demonstrations are not explicitly detailed in the provided data.