Data Engineer - QuantumBlack
McKinsey & Company
Data Science
Jakarta, Indonesia · Kuala Lumpur, Malaysia · Singapore
Posted on Feb 20, 2025
Data Engineer - QuantumBlack
Job ID: 94882
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
You will work on real-world, high-impact projects across a variety of industries. You will have the opportunity to collaborate with QB/Labs teams and 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.
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:
- 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
- Have the opportunity to 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 clients data landscape and assess data quality
- Create and manage data environments and ensure information security standards are maintained at all times
- Design and build data pipelines for machine learning that are robust, modular, scalable, deployable, reproducible, and versioned
- Help to build and maintain the technical platform for advanced analytics engagements, spanning data science and data engineering work
Your Growth
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.
Who you are: You 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.
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
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
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.
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Job Skill Group - N/A
Job Skill Code - DSAD - Data Engineer II
Function -
Industry -
Post to LinkedIn - Yes
Posted to LinkedIn Date - Mon Feb 17 00:00:00 GMT 2025
LinkedIn Posting City - Singapore
LinkedIn Posting State/Province -
LinkedIn Posting Country - Singapore
LinkedIn Job Title - Data Engineer - QuantumBlack
LinkedIn Function - Analyst;Consulting
LinkedIn Industry - Management Consulting
LinkedIn Seniority Level - Associate
Job Skill Code - DSAD - Data Engineer II
Function -
Industry -
Post to LinkedIn - Yes
Posted to LinkedIn Date - Mon Feb 17 00:00:00 GMT 2025
LinkedIn Posting City - Singapore
LinkedIn Posting State/Province -
LinkedIn Posting Country - Singapore
LinkedIn Job Title - Data Engineer - QuantumBlack
LinkedIn Function - Analyst;Consulting
LinkedIn Industry - Management Consulting
LinkedIn Seniority Level - Associate