Senior Data Engineer - QuantumBlack Labs

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Who You'll Work With
You will part of our global data engineering community. 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.
You will be part of a product team in QuantumBlack Labs and you will collaborate with our Social, Healthcare and Public Entities (SHaPE) practice in one of our offices in NA. The SHaPE practice is one of 10 industry practices within the firm and has a mission of measurably improving individuals' lives, livelihoods and health and creating safer and more just communities around the world. SHaPE serves governments, donors, healthcare payors/providers and non-governmental organizations on topics including health, public finance, education, defense, economic development and beyond.
McKinsey's Social, Healthcare and Public Entities practice fosters innovation driven by advanced analytics, user experience design thinking, predictive forecasting and new product development. We are a community of entrepreneurs within McKinsey dedicated to using technology to accelerate meaningful impact for our clients. Through self-service access to analytics and data, software as a service solutions, strategic acquisitions and a vibrant ecosystem of alliances, we are redefining what it means to work with McKinsey.
You will work with software engineers, product managers, data scientists, data engineers and designers to create innovative products and new technologies that facilitate, accelerate and enable the development and deployment of Artificial Intelligence / Machine Learning solutions at scale in production.
Operating like an "internal start up", we've already done a lot to be proud of, such as:

  • Designing products that can explain complex data landscapes and insights to our users
  • Building frameworks and libraries for data scientists and data engineers to work in large-scale, complex projects.
  • Codifying the methodology by which we deliver advanced analytics projects to our clients and the tooling needed to support them


What our colleagues particularly enjoy about QuantumBlack Labs:

  • Autonomy- Your users will be next to you, giving you unparalleled insight into key problems and the ability to design solutions iteratively, with literally rapid feedback. The fact that our developers have such good access to users make them great candidates to feed into the product lifecycle and suggest the next big thing!
  • Variety & Ownership Mindset- You'll be part of an ecosystem of very different products, providing unique learning and development opportunities. You'll not be just a data scientist but a core part of the product team driving product decisions using your engineering creativity, where you'll interact with users, work with designers and product managers, give presentations and talks. Our team frequently engage in efforts they are passionate about outside their core product team, such as our Analytics for Social Good initiative, sharing their experience during Lightning Talks, joining our Toastmasters group, and many others.
  • A Collaborative, Multi-disciplinary Environment- Our teams include machine learning engineers, creative technologists, product managers, and designers with various experience spikes who work collaboratively and are passionate about their work.


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.
What You'll Do
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
  • Understand clients data landscape and assess data quality
  • Map data fields to hypotheses and curate, wrangle and prepare data for use in advanced analytics models
  • Have the opportunity to contribute to R&D projects and internal asset development
  • Contribute to cross-functional problem-solving sessions with your team and generate assets to impact clients, from data owners and users to C-level executives, to address their needs and build impactful analytics solutions


Our tech Stack:
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!
What you will benefit from:

  • Real-World Impact- No project is ever the same, we work with top-tier clients across multiple sectors, providing unique learning and development opportunities internationally.
  • Fusing Tech & Leadership- We work with the latest technologies and methodologies and offer first-class learning programs at all levels.
  • Multidisciplinary Teamwork- Our teams include data scientists, engineers, project managers, UX and visual designers who work collaboratively to enhance performance.
  • Innovative Work Culture- Creativity, insight, and passion come from being balanced. We cultivate a modern work environment through an emphasis on wellness, insightful talks, and training sessions.
  • Striving for Diversity- With colleagues from over 40 nationalities, we recognize the benefits of working with people from all walks of life.
  • Continuous development and progression- We offer an extensive choice of training sessions, ranging from workshops to international conferences, tailored to your needs as well as a personal mentorship system. We have multiple career paths and geographic locations to evolve within the firm.
  • Global community- you'll learn from colleagues around the world by connecting both internally and externally through our various hosted meet-ups.
  • Healthcare Efficiency- We helped a healthcare provider improve their clinical trial practices by identifying congestion in diagnostic testing as a key indicator of admissions breaches.


Visit our Careers site to watch our video and read about our interview processes and benefits.
Qualifications

  • Degree in computer science, engineering, mathematics, or equivalent work 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 production-grade data pipelines for advanced analytics use cases
  • Experience working across structured, semi-structured, and unstructured data
  • Practical knowledge of continuous delivery concepts and best practices applied to data pipelines and ML models
  • Hands on experience leveraging distributed computing frameworks (e.g. Spark, Dask), cloud platforms (e.g. AWS, Azure, GCP), containerization, and analytics libraries (e.g. pandas, NumPy, matplotlib)
  • Ability to scope projects, define workstreams, and effectively lead and mentor more junior colleagues
  • Commercial client-facing or senior stakeholder management experience would be a plus
  • Willingness to travel
  • There is flexibility to hire at data engineer or senior data engineer level based on candidate experience
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