Senior Data Engineer - QuantumBlack at QuantumBlack, AI by McKinsey. (Houston, TX)

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Who You'll Work With
You will be 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
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 our 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'll 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.

Visit our Careers site to watch our video and read about our interview processes and benefits.
  • 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 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, inc. DevOps, DataOps, and MLOps would be considered a plus
  • 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)
  • Ability to scope projects, define workstreams, and effectively lead and mentor more junior colleagues
  • Commercial client-facing or senior stakeholder management experience
  • Willingness to travel
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