McKinsey & Company Hiring for Data Engineer at Gurgaon, Haryana, India Full Time

Job Description

Qualifications

• Bachelor’s degree in computer science or related field; master’s degree is a plus
• 3+ years of relevant work experience
• Experience with at least two of the following technologies: Python, Scala, Java
• Strong proven experience on distributed processing frameworks (Spark, Hadoop, EMR) and SQL is very much expected
• Commercial client-facing project experience is helpful, including working in close-knit teams
• Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets
• Confirmed ability in clearly communicating complex solutions
• Understandings on information security principles to ensure compliant handling and management of client data
• Experience and interest in Cloud platforms such as: AWS, Azure, Google Platform or Databricks
• Extraordinary attention to detail

Who You’ll Work With

You will be based in Gurugram as part of a global data engineering community and you will work in cross-functional and Agile project teams alongside project managers, data scientists, machine learning engineers, other data engineers and industry experts. You will work hand in hand with our clients from data owners and users to C-level executives.
You’ll be aligned to one of our practice Pharma & Medical Products (PMP) or Global Energy & Materials (GEM) to work on similar industry clients.
PMP (Pharma): Our PMP practice focuses on helping clients bring life-saving medicines and medical treatments to patients. You will work with Advances Analytics team across Research & Development (R&D), Operations, and Commercial to build and scale digital and analytical approaches. This Practice is one of the fastest growing practices and is comprised of a tight-knit community of consultants, research, solution, data, and practice operations colleagues across the Firm. PMP is also one of the most globally connected sector Practices, offering ample global exposure.
GEM (Global Energy & Materials): You will work with our Advanced Analytics team as part of our Global Energy & Materials (GEM) practice. Our GEM practice supports clients in a wide range of industries including chemicals, steel, mining, pulp & paper, electric power and oil & gas, among other on the way to operational excellence. Energy and materials industries are big and important to the world’s economy and you as a key player will face significant challenges such as meeting growing demands, operating productively, and managing gigantic capital investments. McKinsey has an unparalleled reputation in these industries across the world, and today serves most of the top players globally.
GEMx and PMPx is the practice’s assetization arm focused on creating reusable digital and analytics assets to support our client work. They work directly with clients to build and scale digital and analytical approaches to addressing their most persistent priorities. E.g., PMPx builds and operates tools that support senior executives in pharma and device manufacturers, for whom evidence-based decision-making and competitive intelligence are paramount. Over the last few years, McKinsey has developed strong digital and analytics capabilities, to help our clients transform their businesses. Being one of the largest groups in the firm, this team comprises of data scientists, data engineers, product managers, tech architects, design experts, amongst others. As part of our group, you will join a global practice solving problems for large organizations in our GEM practice and building their capabilities for sustained impact.

What You’ll Do

You are a highly collaborative individual and enjoy solving problems that focus on adding business value. You have a sense of ownership and enjoy hands-on technical work. Our values resonate with yours.
As a Data Engineer, you will:

• Collaborate with business stakeholders, data scientists and internal teams to build and implement extraordinary domain focused data products (re-usable asset) and solutions and delivering them right to the client.
• Develop deep domain understanding • Use new and creative techniques to deliver impact for our clients as well as R&D projects
• Help to build and maintain the technical platform for advanced analytics engagements, spanning data science and data engineering work
• Design and build data pipelines for machine learning that are robust, modular, scalable, deployable, reproducible, and versioned
• Create and manage data environments and ensure information security standards are maintained at all times
• Understand clients data landscape and assess data quality
• Map data fields to hypotheses and curate, wrangle, and prepare data for use in advanced analytics models
• Have the opportunity to contribute to R&D projects and internal asset development
• Contribute 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 solutions

Our 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 learn:

• How successful projections on real world problems across a variety of industries are completed through referencing past deliveries of end to end pipelines.
• Build products alongside the Core engineering team and evolve the engineering process to scale with data, handling complex problems and advanced client situations.
• Be focused on the wrangling, clean-up and transformation of data by working alongside the Data Science team which focuses on modelling the data.
• Using new technologies and problem-solving skills in a multicultural and creative environment.

You will work on the frameworks and libraries that our teams of Data Scientists and Data Engineers use to progress from data to impact. You will guide global companies through data science solutions to transform their businesses and enhance performance across industries including healthcare, automotive, energy and elite sport.

• Real-World Impact – We provide 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.

Visit our Careers site to watch our video and read about our interview processes and benefits.