Senior Data Engineer - QuantumBlack, AI by McKinsey

McKinsey; Monterrey; Hybrid; MXN 900,000 - 1,500,000; Full time

Job summary

McKinsey & Company is looking for a data engineer in Monterrey to design scalable data foundations for AI applications. You will collaborate with data scientists and ML engineers to build production pipelines, handle data governance, and implement robust, scalable AI features with attention to latency and cost.

You will work in cross-functional teams across industries, applying best practices in data security and MLOps, while growing as a client-facing technologist in a global firm.

Qualifications

• Degree in CS/Engineering or equivalent experience.
• 5+ years in data engineering with leadership and mentorship.
• Expert Python and SQL; polyglot with Scala/Java when needed.

Responsibilities

• Design and maintain scalable data pipelines for AI systems.
• Lead AI feature implementations end-to-end with guardrails.
• Ensure data security, governance, and compliant RBAC controls.

Skills

Python

SQL

Scala/Java

Agentic AI

Generative AI

Machine Learning

Business Intelligence

Prompt design

RAG

Embeddings

Vector databases

LangChain

Databricks

Spark

Airflow

Dagster

Kedro

CI/CD for data workflows

Terraform

AWS

Azure

GCP

Data security

Governance

RBAC

PII/PHI handling

CICD for data

Coding agents

English

Spanish

Education

Degree in Computer Science/Engineering

Tools

Spark

LangChain

Databricks

Dask

Airflow

Dagster

Kedro

Terraform

LangSmith

Opik

Langfuse

Cursor

Claude Code

Codex

Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.

YOUR IMPACT

You will build the foundational data infrastructure that powers cutting-edge AI applications leveraging LLMs, retrieval systems, workflows, and emerging agentic architectures. You will design and maintain scalable data pipelines, manage secure data environments, and prepare data for AI-driven systems while collaborating with cross-functional teams and clients. You’ll tackle real-world challenges by contributing to the development of next-generation AI systems and grow as a technologist by working alongside diverse experts across industries. You will design and build the scalable, reproducible data components essential for machine learning, agentic, and autonomous AI systems. You’ll assess data landscapes, apply data quality fundamentals, and prepare data for AI solutions. Additionally, you’ll learn to translate simple hypotheses into engineered features, manage secure data environments, and contribute to R&D initiatives focused on innovating and scaling next-generation AI capabilities. Your work will help solve some of the most complex and high-impact challenges facing clients across industries. Collaborating across QuantumBlack, AI by McKinsey and QuantumBlack Labs teams, you’ll help develop innovative AI capabilities and scalable enterprise solutions. You’ll help build robust data foundations for scalable, production-ready AI systems. Your contributions will directly support the firm’s ability to accelerate AI adoption, solve complex business problems at scale, and enable clients to achieve meaningful, lasting impact. You’ll be based in Monterrey as part of our global Data Engineering community. Working in cross-functional Agile teams, you’ll collaborate closely with Data Scientists, Machine Learning Engineers, and industry experts to deliver AI solutions. By partnering with clients from data owners to C-level executives you’ll help solve complex problems that drive tangible business value and begin to build your skills as a client-facing technologist. You will have a unique opportunity to grow at the forefront of AI, data engineering, and emerging agentic technologies. You’ll develop expertise at the intersection of technology and business by tackling diverse challenges in the evolving AI landscape. Working alongside multidisciplinary teams, you’ll gain a holistic understanding of how data engineering enables advanced AI while collaborating with some leading AI and data experts in the industry.

YOUR GROWTH

• Continuous learning:Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
• A voice that matters:From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
• Global community:With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
• World-class benefits:On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

YOUR QUALIFICATIONS AND SKILLS

• Degree in Computer Science/Engineering, or equivalent experience
• 5+ years of relevant professional experience in a data engineering role, with experience leading technical workstreams, mentoring junior engineers, and driving the adoption of software engineering best practices within a team
• Expert-level proficiency in Python and SQL and the ability to work in polyglot environments (Scala, Java) when required by client enterprise systems
• Strong experience building Agentic AI, Generative AI, Machine Learning, and Business Intelligence systems, including prompt design, retrieval-augmented generation (RAG), embeddings, vector databases, context construction, and output handling in production workflows using modern frameworks (Spark, LangChain, Databricks, Dask, Airflow, Dagster, Kedro, etc.)
• Ability to lead the implementation of AI features end to end, with sound judgment around model behavior, evaluation, reliability, guardrails, and the trade-offs between quality, latency, and cost
• Experience implementing robust data security and governance controls, including managing PII/PHI, authentication, and role-based access control (RBAC)
• Deep knowledge of MLOps/LLMOps including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform) across cloud providers (AWS, Azure, GCP)
• Exceptional time management and ability to own technical workstreams autonomously
• Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus
• Strong communication skills, both verbal and written, in English and Spanish

FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.