Data Engineer - QuantumBlack

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McKinsey & Company, Inc.

Daerah Khusus Ibukota Jakarta

IDR 200,000,000 - 300,000,000

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Job description

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 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 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