Data Engineer - QuantumBlack, AI by McKinsey
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. 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.
- Degree in Computer Science, Engineering, Mathematics, or equivalent experience
- 0-2+ years of experience building data pipelines in a professional setting (for example, internship) would be considered a plus
- Ability to write clean and maintainable code in an object-oriented language, e.g., Python, Scala, Java
- Familiarity with analytics libraries (e.g. pandas, numpy, matplotlib), distributed computing frameworks (e.g. Spark, Dask), and cloud platforms (e.g. AWS, Azure, GCP)
- Exposure to software engineering concepts and best practices, inc. DevOps, DataOps and MLOps will be beneficial
- 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.
- Strong communication skills, both verbal and written, in English and French, with the ability to adjust your style to suit different perspectives and seniority levels
- Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment.
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