Data Engineer I

Who You'll Work With

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. 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

As a Data Engineer I at McKinsey & Company, you will play a key role in designing, building, and deploying scalable data pipelines and infrastructure that enable our analytics and AI solutions.

You will work closely with product managers, developers, asset owners, and client stakeholders to turn raw data into trusted, structured, and high-quality datasets used in decision-making and advanced analytics.

Your core responsibilities will include:

• Developing robust, scalable data pipelines for ingesting, transforming, and storing data from multiple structured and unstructured sources using Python/SQL.
• Creating and optimizing data models and data warehouses to support reporting, analytics, and application integration.
• Working with cloud-based data platforms (AWS, Azure, or GCP) to build modern, efficient, and secure data solutions.
• Contributing to R&D projects and internal asset development.
• Contributing to infrastructure automation and deployment pipelines using containerization and CI/CD tools.
• Collaborating across disciplines to integrate data engineering best practices into broader analytical and generative AI (gen AI) workflows.
• Supporting and maintaining data assets deployed in client environments with a focus on reliability, scalability, and performance.
  
  

Furthermore, you will have opportunity to explore and contribute to solutions involving generative AI, such as vector embeddings, retrieval-augmented generation (RAG), semantic search, and LLM-based prompting, especially as we integrate gen AI capabilities into our broader data ecosystem.

Your Qualifications and Skills

• Bachelor’s degree in computer science, engineering, mathematics, or a related technical field (or equivalent practical experience).
• 3+ years of experience in data engineering, analytics engineering, or a related technical role.
• Strong Python programming skills with demonstrated experience building scalable data workflows and ETL/ELT pipelines.
• Proficient in SQL with experience designing normalized and denormalized data models.
• Hands-on experience with orchestration tools such as Airflow, Kedro, or Azure Data Factory (ADF).
• Familiarity with cloud platforms (AWS, Azure, or GCP) for building and managing data infrastructure.
• Discernable communication skills, especially around breaking down complex structures into digestible and relevant points for a diverse set of clients and colleagues, at all levels.
• High-value personal qualities including critical thinking and creative problem-solving skills; an ability to influence and work in teams.
• Entrepreneurial mindset and ownership mentality are must; desire to learn and develop, within a dynamic, self-led organization.
• Hands-on experience with containerization technologies (Docker, Docker-compose).
• Hands on experience with automation frameworks (Github Actions, CircleCI, Jenkins, etc.).
• Exposure to generative AI tools or concepts (e.g., OpenAI, Cohere, embeddings, vector databases).
• Experience working in Agile teams and contributing to design and architecture discussions.
• Contributions to open-source projects or active participation in data engineering communities.