Data & Analytics Senior Data Engineer

About the role

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

Qualifications

• Data engineering: 4+ years of experience in applied data engineering, with a strong track record delivering scalable, production-grade data solutions
• Mastery of data modeling, ETL/ELT pipeline design, and working with large-scale structured and unstructured datasets
• Strong Python and SQL skills; fluency in core data engineering libraries (e.g., PySpark, Apache Airflow) and familiarity with Big Data tools such as Spark or Scala
• Hands-on experience designing and deploying data solutions on Azure (preferred) or another major cloud platform (e.g., AWS, GCP); familiarity with on-prem platforms such as Microsoft SQL Server
• Hands-on experience with APIs (e.g., FastAPI), containerization (Docker, Kubernetes), DevOps practices, Git, and CI/CD pipelines
• Hands-on experience with Microsoft Fabric across multiple workloads (e.g., Data Factory, Lakehouse, semantic models, Power BI)
• Familiarity with building and deploying cloud-based analytics web applications is preferred
• Familiarity with one of the cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lake architecture is preferred
• AI Engineering: Hands-on experience developing and deploying LLM-based applications in production, including RAG pipelines, prompt engineering, and LLM evaluation
• Experience designing agentic AI systems (e.g., multi-agent orchestration, or automation workflows) using frameworks such as LangChain or equivalent
• Familiarity with at least one major cloud AI platform (Microsoft Foundry, AWS Bedrock, or GCP Vertex AI) and associated deployment patterns
• Familiarity with understanding of LLM evaluation frameworks (e.g., Ragas, LangSmith) and retrieval quality assessment is preferred
• Familiarity with core agentic AI and LLM libraries (e.g., Transformers, LangGraph, Pydantic AI) and experience applying them in production settings is preferred
• Stakeholder Engagement: Ability to understand and articulate requirements to technical and non-technical audiences, working alongside data science, engineering, and consulting teams
• Prior experience in strategic consulting is preferred; exposure to one or more of L.E.K.’s core sectors (life sciences, healthcare, consumer, industrials, TMT) is a strong plus
• Strong problem-solving skills with the ability to translate business needs into technical solutions; comfortable working at pace in a fast-paced, entrepreneurial environment with a high degree of ownership