Houston, New York, United States
Job Details
Full job description
Job ID: 102807
As an associate, you will join a client service team and take ownership of a workstream to solve some of the toughest challenges our clients face.
Houston
Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.
YOUR IMPACT
As a Data Engineer II, you will apply engineering frameworks and best practices to design and build core data frameworks that support our client service organizations.
Your work will enable software capabilities utilized by data engineers, data scientists, consulting teams, and external clients, driving innovation and efficiency across diverse teams.
In this role, you will design and build the technical backbone for advanced analytics engagements. You will create robust, scalable, and reproducible data pipelines for machine learning, curate and prepare data for advanced models, and manage secure data environments. You will also contribute to R&D projects and help develop innovative internal assets and frameworks. You will help to shift our model toward asset-based consulting and is a foundation for and expands our investment in our entrepreneurial culture.
Chemicals practice is a global network of chemical experts and practitioners. At any point in time, approximately 250 consultants are involved in chemical-related client projects. In the past five years alone, our Chemicals practice has supported clients across the world on more than 1,000 strategic, operations, commercial and organization projects.
Powerful forces are reshaping the chemicals industry. As a result, the formula for success in its market is changing. Our industry experience and global reach make us uniquely positioned to help our clients address evolving challenges — and capture new opportunities within the chemicals industry.
Your work will have a tangible impact on real-world, high-stakes projects. By building technology assets for internal and external clients, you will help shape how organizations leverage data to achieve their goals, supporting McKinsey’s shift toward asset-based consulting and delivering lasting value.
You will be based in one of our global hubs as part of our advanced analytics and data engineering community. You will work in cross-functional Agile teams, collaborating with data scientists, machine learning engineers, project managers, and industry experts to create innovative solutions and assets that help clients unlock the full potential of their data.
At McKinsey, you will have the freedom to innovate and grow as a technologist and leader. You will work with leading technologies, collaborate with diverse, multidisciplinary teams, and gain a holistic perspective on AI and data engineering, positioning yourself at the forefront of innovation.
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. 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
Undergrad or Advanced degree in a quantitative field like computer science, machine learning, applied statistics or mathematics, or equivalent experience
2-5+ years of relevant experience
Proven experience building data pipelines in production for advanced analytics use cases
Experience working across structured, semi-structured and unstructured data
Familiarity with distributed computing frameworks, cloud platforms, containerization, and analytics libraries
Exposure to software engineering concepts and best practices, including DevOps, DataOps and MLOps preferred
While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels