Overview
Senior Data Engineer - QuantumBlack role at QuantumBlack, AI by McKinsey.
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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 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, Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more.
As a Senior Data Engineer, you will:
- Own the technical platform for advanced analytics engagements, spanning data science and data engineering work
- Design and build data pipelines for machine learning that are robust, modular, scalable, deployable, reproducible, and versioned
- Create and manage data environments and ensure information security standards are maintained at all times
- Own and be accountable for the delivery of technical work streams while also mentoring and guiding more junior colleagues
- Apply knowledge about clients data landscape and assess data quality
- Design and build GenAI applications (RAG, Agentic AI, etc) collaboratively with data scientists
- Have the opportunity to contribute to R&D projects and internal asset development
- 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
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 Qualifications and Skills
- Degree in computer science, engineering, mathematics, or equivalent experience
- 5+ 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
- Practical knowledge of software engineering concepts and best practices
- Ability to scope projects, define workstreams, and effectively lead and mentor more junior colleagues
- Familiarity with distributed computing frameworks (e.g. Spark, Dask), cloud platforms (e.g. AWS, Azure, GCP), containerization, and analytics libraries (e.g. pandas, NumPy, matplotlib)
- Commercial client-facing or senior stakeholder management experience
Seniority level
Employment type
Job function
- Consulting
- Industries: Business Consulting and Services
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