Senior Data Engineer

About L.E.K. Consulting:

L.E.K. Consulting is a premier global strategy consulting firm that partners with clients to solve their most critical business challenges and deliver high-impact outcomes. We bring deep industry expertise and rigorous, evidence-based insight to global corporations, growth companies and private equity investors, helping them turn strategy into action.

How do we deliver impact? It’s the people. We hire exceptional individuals and invest in their growth through hands-on client work, close collaboration and a culture of ownership, inclusion and continuous learning. Across every level, curiosity unites us and challenge excites us.

Founded more than 40 years ago, L.E.K. employs more than 2,200 professionals worldwide and is consistently recognized as one of the industry's best firms to work for. For more information,  the Role:

We are seeking a Senior Data Engineer with deep expertise in data engineering and a strong working command of AI and LLM tech stacks. This role sits within our Data Science & Engineering team and operates at the intersection of large-scale structured and unstructured data, infrastructure and AI while building the pipelines, platforms, and apps that power client engagements and L.E.K.'s proprietary analytical products The ideal candidate brings fluency in production data engineering (e.g., cloud platforms, pipelines, warehousing, and scalable app deployment) and in building and shipping LLM-based and agentic AI solutions.

You will work directly with clients across multiple industries, translating complex technical work into measurable commercial outcomes, owning delivery across client engagements and internal IP development while working with data scientists, strategy consultants, and client teams to build solutions that create high client impact Responsibilities:

Client engagements:  Lead end-to-end data engineering and AI/ML projects from conceptualization through deployment in clients' cloud environments, optimizing for scalability, performance, and reliability Design and deliver data pipelines, data models, and infrastructure that underpin analytical and AI solutions for client use cases

Support clients in defining and executing data and AI strategies, translating business objectives into actionable technical roadmaps and governance frameworks

Lead or contribute to agentic AI engagements, designing and deploying multi-agent architectures and automation workflows that deliver measurable client outcomes

Support technology due diligence engagements, assessing data infrastructure, AI/ML capabilities, engineering practices, and technical risks of target organizations

Guide clients through the interpretation of analytical outputs and integration of data-driven insights into their business workflows Client / business development:
Support Managing Directors in developing and scoping client proposals where data engineering and AI capabilities are central to delivery Serve as the technical interface between the Data Science & Engineering team, consulting partners, and clients while ensuring alignment on fit, feasibility, and delivery expectations

Translate technical requirements, outputs, and constraints into clear, actionable language for client-facing presentations and proposals

Support the design and commercialization of new offerings across data strategy, AI strategy, agentic AI, and LLM-powered analytics

Contribute to internal enablement by keeping Managing Directors informed of current data strategy and AI capabilities Capability development:

Drive development of scalable, production-grade data pipelines and ETL/ELT processes that feed L.E.K.'s proprietary analytical products and client-facing tools Build and maintain cloud data infrastructure (e.g., warehouses, data lakes, and data models) that support both internal service lines and bespoke client solutions Develop AI-powered analytical applications, leveraging LLMs, RAG architectures, and ML techniques to solve complex client problems Champion best-in-class engineering practices in data quality, CI/CD, containerization, and scalable architecture across all IP assets Stay current on best-in-class data engineering tooling, cloud platforms, and AI/LLM frameworks;

contribute to the D&A technical roadmap, including platform architecture and engineering standards Proactively identify new use cases where data infrastructure or AI can deliver outsized value for clients or strengthen internal firm capabilities Collaborate with data…