Senior Lead Data Engineer

Who We AreAt Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world's leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people-Kyndryls-that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.

The RoleKyndryl is a global, largely remote company, where you join People and Workforce Analytics professionals made up of business translators, data scientists, analysts and developers. We are fast, flat, and focused: you will engage with senior leadership, a diverse group of HR professionals, fellow data scientists and analysts as well as business leaders to ensure our insights are both scientifically rigorous and aligned with our business goals. Your work will directly influence our enterprise strategy and operations and impact tens of thousands of employees. As a Senior Lead Data Engineer for our Workforce Analytics team, you will be a hands on Data Engineer driving integration of our strategic platforms in support the creation of an end-to-end labor optimization model. This model solves for the technical and other skills needed to provide value to our clients, the growth, development and satisfaction of our workforce as well as contractual, legal, geographic and cost constraints. You will create the data model that will best leverage diverse datasets to optimize how we staff, hire, and train our 80,000 Kyndryls.

Specifically you'll be responsible for:

Platform Integration:

Lead the integration of multiple strategic platforms, ensuring seamless data flow and interoperability to support the development of workforce optimization models.

Data Pipeline Development:

Design, build, and maintain robust data pipelines and ETL processes that collect, cleanse, and process data from various sources to create a comprehensive data ecosystem.

Optimization Model:

Collaborate with data scientists, analysts, and other stakeholders to support build and refine optimization models that predict skills gaps and recommend actions such as upskilling, hiring, or engagement of workers.

Data Management and Architecture:

Develop scalable data architecture solutions that ensure high performance, reliability, and accessibility of workforce data across the organization.

Collaboration and Stakeholder Management:

Work closely with cross-functional teams including HR, business units, and IT to align data engineering efforts with business needs and strategic goals.

Automation and Continuous Improvement:

Implement automation in data processes to improve efficiency and accuracy, continuously exploring new tools and technologies to enhance data integration and modeling capabilities.

Data Governance and Quality:

Establish data governance practices and ensure data quality, integrity, and security are maintained across all platforms.

Your Future at KyndrylEvery position at Kyndryl offers a way forward to grow your career. We have opportunities that you won't find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.

Who You AreYou're good at what you do and possess the required experience to prove it. However, equally as important - you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused - someone who prioritizes customer success in their work. And finally, you're open and borderless - naturally inclusive in how you work with others.

Required Skills and Experience5-8+ years of relevant data engineering experienceStrong experience in building and maintaining ETL/ELT data pipelinesProficiency in Python and SQL for data processingHands-on experience with data integration across multiple enterprise platformsSolid understanding of data architecture and data modelingExperience with cloud platforms (AWS/Azure/GCP) and modern data toolsKnowledge of data governance, quality, and security practicesAbility to work with large, complex, and diverse datasetsExperience collaborating with data scientists, analysts, and business stakeholdersStrong problem-solving and business translation skillsPreferred Skills and ExperienceExperience supporting optimization or predictive analytics modelsFamiliarity with machine learning pipelines or MLOps conceptsKnowledge of workforce/HR analytics and talent data systemsExperience with real-time or streaming data technologies (e.g., Kafka)Hands-on with HR platforms like WorkdayExposure to CI/CD, automation, and Infrastructure as CodeAbility to influence business strategy using data insightsExperience leading large-scale data integration initiativesStrong communication skills for engaging senior leadershipComfortable working in remote, global, cross-functional teamsBeing YouThe \