Data Engineer Ii Job in Mckinsey & Company

Your Impact

As a Data Engineer at QuantumBlack, you will collaborate with stakeholders, data scientists, and internal teams to develop and implement impactful data products and solutions. Your key responsibilities will include building and maintaining technical platforms for advanced analytics, designing scalable and reproducible data pipelines for machine learning, and ensuring information security within data environments.

You will assess clients' data quality, map data fields to hypotheses, and prepare data for use in analytics models. Additionally, you will contribute to R&D projects, internal asset development, and participate in cross-functional problem-solving sessions with a variety of stakeholders, including C-level executives, to create innovative analytics solutions.

You will be based in Gurugram, joining a global data engineering community, and work within cross-functional and Agile project teams alongside project managers, data scientists, machine learning engineers, other data engineers, and industry experts. You will collaborate directly with our clients, ranging from data owners and users to C-level executives.

You will be aligned with one of our industry-focused practices: Pharma & Medical Products (PMP) or Global Energy & Materials (GEM). In these practices, you ll work on solving the most critical challenges for our clients in these sectors. PMP focuses on advancing the development and delivery of life-saving medicines and medical treatments, while GEM supports industries like chemicals, steel, mining, and energy to achieve operational excellence.

GEMx and PMPx, the assetization arm of these practices, focus on creating reusable digital and analytics assets to support client work. As part of this team, you will help shape impactful solutions for large organizations, developing capabilities for sustained impact.

Your Growth

In this role, you will contribute to the frameworks and libraries that our teams of Data Scientists and Engineers use to progress from data to meaningful impact. You will have the opportunity to guide global companies through data science solutions, helping them transform and enhance performance across industries including healthcare, automotive, energy, and elite sports.

• Real-World Impact: You ll gain unique learning and development opportunities globally.
• Fusing Tech & Leadership: Work with the latest technologies and methodologies, with access to top-tier learning programs.
• Multidisciplinary Teamwork: Collaborate with data scientists, engineers, project managers, UX designers, and more to enhance performance.
• Innovative Work Culture: Creativity, passion, and wellness are central to our modern work environment, which includes insightful talks, training sessions, and a focus on work-life balance.
• Striving for Diversity: We celebrate diversity, with colleagues from over 40 nationalities, appreciating the value that diverse perspectives bring to the workplace.

You are a highly collaborative individual who prioritizes impact over agenda. You enjoy learning from colleagues, challenging ideas thoughtfully, and working together to improve processes and solve problems. You believe in iterative change, experimenting with new approaches, and advancing quickly through constant learning and improvement.

While we value using the right tech for the right task, our team often leverages technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro (our open-source data pipelining framework), Dask/RAPIDS, Docker, Kubernetes, and cloud solutions like AWS, GCP, and Azure.

Your Role as a Data Engineer

• Collaboration: Work with business stakeholders, data scientists, and internal teams to create extraordinary, domain-focused data products (reusable assets) and deliver them to clients.
• Domain Expertise: Develop deep understanding of client industries and use creative techniques to deliver meaningful impact.
• Technical Platforms: Build and maintain technical platforms for advanced analytics engagements, spanning both data science and data engineering work.
• Data Pipelines: Design and implement robust, modular, scalable, deployable, and reproducible data pipelines for machine learning.
• Data Management: Ensure the security of data environments and compliance with information security standards.
• Data Wrangling: Assess data quality, map data fields to hypotheses, and prepare data for analytics models.
• Contribute to R&D: Participate in internal asset development and contribute to R&D projects to drive innovation.
• Cross-functional Problem Solving: Collaborate with internal teams and clients, including data owners and C-level executives, to create impactful analytics solutions.

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.
• Proficiency in at least one programming language such as Python, Scala, or Java.
• Strong experience with distributed processing frameworks (e.g., Spark, Hadoop, EMR) and SQL.
• Experience in commercial client-facing projects, particularly in close-knit teams.
• Ability to work with structured, semi-structured, and unstructured data, and identify linkages across disparate data sets.
• Clear communication skills to explain complex solutions effectively.
• Understanding of information security principles to ensure compliant handling of client data.
• Experience with cloud platforms (AWS, Azure, Google Cloud, Databricks) is highly desirable.
• Experience with CI/CD processes using GitHub Actions, CircleCI, or similar, and end-to-end pipeline development including application deployment is a plus.