Bangalore, Karnataka, India
Information Technology
Other
McKinsey & Company
Overview
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 at QuantumBlack, you will collaborate with stakeholders, data scientists, and internal teams to develop and implement data products and solutions. Key responsibilities include building and maintaining technical platforms for advanced analytics, designing scalable and reproducible data pipelines for machine learning, and ensuring information security in data environments.
You will assess clients' data quality, map data fields to hypotheses, and prepare data for analytics models.
Additionally, you will contribute to R&D projects, internal asset development, and cross-functional problem-solving sessions with various stakeholders, including C-level executives, to create impactful analytics solutions.
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 will be aligned to one of our practice Pharma & Medical Products (PMP) or Global Energy & Materials (GEM) to work on similar industry clients.
Our PMP practice focuses on helping clients bring life-saving medicines and medical treatments to patients. You will work with the Advanced 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.
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. 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.
Your Growth
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.
You are a highly collaborative individual who is capable of laying aside your own agenda, listening to and learning from colleagues, challenging thoughtfully and prioritizing impact. You search for ways to improve things and work collaboratively with colleagues. You believe in iterative change, experimenting with new approaches, learning and improving to move forward quickly.
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!
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
Visit our Careers siteto watch our video and read about our interview processes and benefits.
Your qualifications and skills
- Bachelor's degree in computer science or related field; master's degree is a plus
- 2-5 years of relevant work experience
- Experience with at least one 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
- Proven ability in clearly communicating complex solutions; strong attention to detail
- Understanding of 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
- Good to have experience in CI/CD using GitHub Actions or CircleCI or any other CI/CD tech stack and experience in end to end pipeline development including application deployment
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