Senior Data Platform Architect – AI & ML Pipelines

McKinsey; Chicago (IL); On-site; USD 217,000 - 220,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits

Mentorship and coaching

Job summary

McKinsey & Company in the United States seeks a senior data engineering leader to architect enterprise data and AI platforms, drive scalable pipelines, and mentor teams across client engagements. You will work with data scientists and engineers, shaping solutions for diverse industries.

Based in North America, you will collaborate with clients and cross-functional teams, contribute to R&D, and advance innovation within the McKinsey data engineering community while traveling as needed.

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 technical teams and architect data platforms.
• Build scalable pipelines for enterprise analytics.
• Mentor junior colleagues.
• Collaborate with clients and cross-functional teams.
• Drive AI projects across industries and ensure security standards.

Skills

Data platform architecture

Mentoring

DevOps

DataOps

MLOps

Python/Scala/Java

Stakeholder management

Communication

Time management

Travel

Cloud platforms

Distributed computing (Spark)

Education

Degree in Computer Science, Engineering, Mathematics, or equivalent experience

Tools

Databricks

Airflow

SQL

PySpark

Kedro

RAPIDS

Docker

Kubernetes

Job description

McKinsey & Company in the United States seeks a senior data engineering leader to architect enterprise data and AI platforms, drive scalable pipelines, and mentor teams across client engagements. You will work with data scientists and engineers, shaping solutions for diverse industries.

Based in North America, you will collaborate with clients and cross-functional teams, contribute to R&D, and advance innovation within the McKinsey data engineering community while traveling as needed.