Data Engineer II - QuantumBlack, AI by McKinsey

McKinsey; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

McKinsey is seeking a technically skilled Data Engineer to build GenAI and ML systems across industries. You will collaborate with Data Scientists, ML Engineers, and cross-functional teams to design robust data pipelines and scalable analytics solutions.

You will work hand-in-hand with clients, data owners, and senior stakeholders to transform data into business value, leveraging cloud platforms and modern data tooling. This role offers growth within a diverse, global environment.

Qualifications

• Degree in computer science, engineering, mathematics, or equivalent experience.
• 2+ years of relevant professional experience.
• Proficient in writing clean, scalable code in Python, Scala, or Java.
• Proven experience building data pipelines in production for analytics use cases.
• Experience working with structured, semi-structured and unstructured data.
• Exposure to DevOps, DataOps and MLOps would be a plus.
• Familiarity with distributed computing frameworks, cloud platforms, containers, and analytics libraries.
• Experience with Big Data platforms and tools like AWS, Azure, GCP and Spark/Kafka/Snowflake.

Responsibilities

• Contribute to cross-functional problem-solving sessions with your team and clients to build impactful analytics solutions.
• Contribute to R&D projects and internal asset development.
• Design and build GenAI applications (RAG, Agentic AI) with data scientists.
• Map data fields to hypotheses and curate, wrangle, and prepare data for use in analytics models.
• Assess data quality and apply knowledge about client data landscape.
• Create and manage data environments, ensuring information security standards.
• Design and build data pipelines for machine learning that are robust, scalable, and reproducible.
• Support the technical platform for analytics engagements across data science and data engineering.
• Collaborate in a global Data Engineering community within cross-functional Agile teams.

Skills

Python

Scala

Java

Data pipelines

Education

Degree in computer science or engineering

Tools

Spark

Kafka

Snowflake

AWS/GCP/Azure

Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.

YOUR IMPACT

You will work on real-world, high-impact projects across a variety of industries. You will collaborate with QuantumBlack, AI by McKinsey and the QuantumBlack Labs team to build complex and innovative ML systems to accelerate our work in AI and help solve business problems at speed and scale. You will experience the best environment to grow as a technologist and a leader. You will develop a sought-after perspective connecting technology and business value by working on real-life problems across a variety of industries and technical challenges to serve our clients on their changing needs. You will be surrounded by inspiring individuals as part of diverse and multidisciplinary teams. You will develop a holistic perspective of AI by partnering with the best design, technical, and business talent in the world as your team members.

• 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
• Contribute to R&D projects and internal asset development
• Design and build GenAI applications (RAG, Agentic AI, etc) collaboratively with data scientists
• Map data fields to hypotheses and curate, wrangle, and prepare data for use in advanced analytics models
• Apply knowledge about client’s data landscape and assess data quality
• Create and manage data environments and ensure information security standards are always maintained
• Design and build data pipelines for machine learning that are robust, modular, scalable, deployable, reproducible, and versioned
• Help build and maintain the technical platform for advanced analytics engagements, spanning data science and data engineering work
• You will be part of our global Data Engineering community, and 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.

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, all while upholding our unwavering commitment to ethics and integrity. 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

• Degree in computer science, engineering, mathematics, or equivalent experience
• 2+ years of relevant professional experience
• Ability to write clean, maintainable, scalable and robust code in an object-oriented language, e.g., Python, Scala, Java, in a professional setting
• Proven experience building data pipelines in production for advanced analytics use cases
• Experience working across structured, semi-structured and unstructured data
• Exposure to software engineering concepts and best practices, inc. DevOps, DataOps and MLOps would be considered a plus
• Familiarity with distributed computing frameworks, cloud platforms, containerization, and analytics libraries (e.g. pandas, numpy, matplotlib)
• Experienced on Big Data platforms and tools like AWS, Azure, GCP and tools like Spark, Kafka, Snowflake, GCS Data Proc, Azure DataFactory, AWS Glue, Apache Beam/Flink, Python/PySpark, etc.
• Commercial client-facing or senior stakeholder management experience would be beneficial

FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.

FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.