Lead Data Engineer - Enterprise AI & ML Platforms

McKinsey

Washington (District of Columbia)

On-site

USD 217,000 - 220,000

Full time

3 days ago

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Benefits offered by this job

Competitive salary

Global community

World-class benefits

Mentorship and development

Job summary

McKinsey in the United States seeks a senior data engineering leader to drive AI platform development, lead technical teams, and partner with clients to deliver scalable analytics solutions across industries.

You will own data pipelines, ensure security, mentor colleagues, and advance R&D within QuantumBlack, AI by McKinsey. This role offers a high-impact environment in North America with cross-functional teams and growth opportunities.

Qualifications

Degree in Computer Science, Engineering, Mathematics, or equivalent experience
10+ years relevant professional experience
Ability to scope projects, define workstreams, and translate roadmaps into sprint goals, milestones, and deliverables within agile and iterative team environments
Proven experience architecting and building enterprise data and AI platforms as well as scalable data pipelines for advanced analytics use cases operating in production
Passion for and track record of effectively leading and mentoring more junior colleagues
Expertise in implementing software engineering best practices to drive enterprise-wide improvement, including DevOps, DataOps, and MLOps
Strong software engineering and data engineering expertise, including distributed computing frameworks (e.g., Spark, Dask), cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), analytics libraries (e.g., pandas, NumPy, matplotlib), and modern data platforms and orchestration tools such as Databricks, Airflow, SQL, PySpark, Kedro, and RAPIDS
Ability to write clean, maintainable, scalable, and robust code in object-oriented languages such as Python, Scala, or Java, and experience supporting the development of junior engineers through collaborative code reviews
Extensive commercial client-facing or senior stakeholder management experience
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
Willingness to travel
Strong communication skills with the ability to adjust your style to suit different perspectives and seniority levels

Responsibilities

Lead multiple technical teams and own the technology stack for enterprise data and AI platforms.
Design and build robust, scalable data pipelines for machine learning while ensuring information security standards are upheld.
Mentor junior colleagues, contribute to R&D projects, and drive innovation within the QuantumBlack, AI by McKinsey Data Engineering community.
Partner with QuantumBlack, AI by McKinsey and QuantumBlack Labs to create innovative ML systems that accelerate AI adoption and solve business problems at speed and scale.
Collaborate with clients from data owners to C-level executives to architect impactful solutions that solve complex business problems and drive value.