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Employer: McKinsey & Company

Expires: 09/17/2021

QUALIFICATIONSUniversity student with a graduation date between December 2021 to June 2022 pursuing a degree in computer science, engineering, mathematics or equivalent experienceAbility to write clean and maintainable code in an object-oriented language (e.g. Python, Scala, Java)Experience building data pipelines in a professional setting (e.g. internship) is a plusFamiliarity with analytics libraries (e.g. pandas, numpy, matplotlib), distributed computing frameworks (e.g. Spark, Dask) and cloud platforms (e.g. AWS, Azure, GCP)Exposure to software engineering concepts and best practices including DevOps, DataOps and MLOps is beneficialWillingness to travelWHO YOU’LL WORK WITHYou will be based in our Boston, Chicago, or New York offices, and will part of our global data engineering community. You will work in cross-functional Agile project teams alongside data scientists, machine learning engineers, other data engineers, project managers, and industry experts. You will work hand-in-hand with our clients, from data owners, users, and fellow engineers to C-level executives.Who you areYou are a highly collaborative individual who wants to solve problems that drive business value. You have a strong sense of ownership and enjoy hands-on technical work. Our values resonate with yours.WHAT YOU’LL DOAs a Junior Data Engineer, you will:Help to build and maintain the technical platform for advanced analytics engagements, spanning data science and data engineering workDesign and build data pipelines for machine learning that are robust, modular, scalable, deployable, reproducible, and versionedCreate and manage data environments and ensure information security standards are maintained at all timesUnderstand clients data landscape and assess data qualityMap data fields to hypotheses and curate, wrangle, and prepare data for use in advanced analytics modelsHave the opportunity to contribute to R&D projects and internal asset developmentContribute to cross-functional problem-solving sessions with your team and our clients, from data owners and users to C-level executives, to address their needs and build impactful analytics solutionsOur tech stack: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!What you’ll benefit from:Real-World Impact – No project is ever the same, we work with top-tier clients across multiple sectors, providing unique learning and development opportunities internationally.Fusing Tech & Leadership – We work with the latest technologies and methodologies and offer first-class learning programs at all levels.Multidisciplinary Teamwork – Our teams include data scientists, engineers, project managers, UX and visual designers who work collaboratively to enhance performance.Innovative Work Culture – Creativity, insight, and passion come from being balanced. We cultivate a modern work environment through an emphasis on wellness, insightful talks, and training sessions.Striving for Diversity – With colleagues from over 40 nationalities, we recognize the benefits of working with people from all walks of life.Continuous development and progression – We offer an extensive choice of training sessions, ranging from workshops to international conferences, tailored to your needs as well as a personal mentorship system. We have multiple career paths and geographic locations to evolve within the Firm.Global community – you’ll learn from colleagues around the world by connecting both internally and externally through our various hosted meet-ups.Non-students can apply to the non-campus version of this role.Visit our Careers site to watch our video and read about our interview processes and benefits