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.

Responsibilities

• 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
• Serving as the technical interface between the Data Science & Engineering team, consulting partners, and clients while ensuring alignment on fit, feasibility, and delivery expectations
• Translating technical requirements, outputs, and constraints into clear, actionable language for client-facing presentations and proposals
• Supporting the design and commercialization of new offerings across data strategy, AI strategy, agentic AI, and LLM-powered analytics
• Contributing 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