Data Engineer (Software Implementation)

McKinsey & Company, Inc.; Ciudad de México; Presencial; MXN 1,038,000 - 1,386,000; Jornada completa

Descripción de la vacante

A global consulting firm in Mexico City seeks a skilled Data Engineer to join their Source AI team. You will design, build, and maintain data pipelines leveraging Snowflake, ensuring data quality and performance. The ideal candidate has 4+ years of data engineering experience, at least 3 years with Snowflake, and a strong command of SQL and Python. This role offers mentorship and the opportunity to work in a collaborative global environment, providing world-class benefits and a chance to drive significant impact in the procurement space.

Servicios

Comprehensive benefits package

Continuous learning opportunities

Global community engagement

Formación

• 4+ years of experience in data engineering with 3+ years focused on Snowflake.
• Strong command of SQL (ANSI, Snowflake SQL dialect) and Python.
• Experience with semi-structured data (JSON, Avro, Parquet) in Snowflake.

Responsabilidades

• Design, build, and maintain end-to-end data pipelines.
• Develop and enforce data quality frameworks.
• Lead and execute data migrations from legacy systems to Snowflake.

Conocimientos

Snowflake expertise

Data pipeline management

SQL proficiency

Python scripting

Educación

Certified SnowPro Core or Advanced Data Engineer

Herramientas

Snowflake

Amazon S3

DBT

Airflow

Descripción del empleo

Your Growth

Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.

In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have:

• 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 Impact

You will be part of the Source AI team and will have the opportunity to develop a deep understanding of the domain/function.

Source AI is a Gen AI fueled strategic category management platform within Operations practice. It combines internal and external data with McKinsey’s functional and technological industrial expertise to empower category managers to make informed real-time decisions and unlock new opportunities. It is one of the fastest growing solutions in McKinsey, offering one of a kind exposure to define future the of procurement powered by AI. The Source AI team works with clients globally to deliver value for procurement functions supported by McKinsey’s extensive expert network.

You will work closely with consultants and senior leaders serving clients in North America and Latin America. As a Data Engineer in Source AI you will have deep expertise in Snowflake and modern data architecture, hands on experience building high-performance data pipelines, ensuring data quality, managing migrations, and handling multiple Snowflake environments in a secure and efficient manner. This is a key role to scale our data ecosystem across domains and geographies.

You will collaborate with cross-functional teams to enhance the platform, ensuring seamless client deployment and continuous upgradation of functionalities, as per client demands. You will lead the analyses on key spend categories to identify opportunities through solutions and work with the practice leaders and experts in different regions to continuously build the solution with new functionalities and knowledge. You will connect with external market solutions and establish partnerships that can deliver value to both parties. As you grow in the role, you will mentor analysts on topics related to procurement analyses and delivery of solutions for clients.

Your qualifications and skills

• Design, build, and maintain end-to-end data pipelines leveraging Snowflake and Amazon S3 for ingestion, transformation, and storage
• Develop and enforce data quality frameworks (validation, anomaly detection, alerts) across ingestion and transformation layers.
• Set up and manage multiple Snowflake environments (Dev, Test, QA, Prod) with proper environment isolation, RBAC, and CI/CD practices.
• Lead and execute data migration initiatives from legacy/on-prem databases to Snowflake.
• Optimize Snowflake performance via clustering, materialized views, query profiling, and result caching.
• Develop and manage Snowflake Streams, Tasks, External Tables, File Formats, Stages, and Pipes for near real-time and batch processing.
• Implement Snowflake Snowpipe for continuous and automated data ingestion from S3.
• Manage and optimize virtual warehouses for performance and cost efficiency.
• Build reusable dbt models, implement modular transformations, and integrate into orchestration tools like Airflow or Dagster.
• Integrate Snowflake with BI tools and downstream applications securely using OAuth/JWT, Service Accounts, and External Functions.
• Apply data governance practices, including row-level security, column masking, and tag-based access control.
• 4+ years of experience in data engineering with at least 3+ years focused on Snowflake.
• Strong command of SQL (ANSI, Snowflake SQL dialect) and Python for scripting and transformation.
• Expertise in managing Snowflake features such as Warehouses, Databases, Schemas, Roles, Snowpipe, Streams & Tasks, External Tables, Data Sharing, Secure Views, Clustering Keys
• Experience with Snowflake Connector for Python, Snowflake REST API, and Snowflake's Native Apps or UDFs.
• Proficiency with CI/CD pipelines for Snowflake using tools like GitHub Actions
• Certified SnowPro Core and/or SnowPro Advanced: Data Engineer.
• Experience working with semi-structured data (JSON, Avro, Parquet) in Snowflake.
• Knowledge of data privacy & governance (e.g., PII handling, GDPR, HIPAA).
• Ability to communicate ideas most effectively in English - both verbally and in writing