Senior Data Engineer - AI & Data Platform Architect

LEK; United States; Hybrid; USD 135,000 - 165,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

Life and disability insurance

401(k) with employer contribution

HSA contributions

Paid time off

Job summary

L.E.K. Consulting is 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, building pipelines, platforms and apps that power client engagements and L.E.K.'s analytical products. You will work with clients across industries, translating complex technical work into measurable commercial outcomes while owning delivery across engagements and internal IP development.

Qualifications

• 4+ years of experience in applied data engineering.
• Mastery of data modeling, ETL/ELT pipeline design, and large-scale data handling.
• Strong Python and SQL skills; fluency with PySpark and Airflow.
• Hands-on experience with cloud platforms (Azure preferred) and containerization (Docker, Kubernetes).

Responsibilities

• Lead end-to-end data engineering and AI/ML projects from conceptualization through deployment.
• Design and deliver data pipelines, data models, and infrastructure for analytical/AI solutions.
• Define and execute data/AI strategies, translating requirements into technical roadmaps.

Skills

Python

SQL

PySpark

Airflow

Azure

Docker

Kubernetes

FastAPI

Microsoft Fabric

Snowflake

Education

Degree in quantitative field

Tools

Azure

AWS

GCP

Snowflake

BigQuery

Redshift

Git

CI/CD

Job description

L.E.K. Consulting is 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, building pipelines, platforms and apps that power client engagements and L.E.K.'s analytical products. You will work with clients across industries, translating complex technical work into measurable commercial outcomes while owning delivery across engagements and internal IP development.