Data Engineer - QuantumBlack, AI by McKinsey

QuantumBlack, AI by McKinsey; Amsterdam; On-site; EUR 50,000 - 90,000; Full time

Job summary

An innovative firm is seeking a Data Engineer to join its dynamic team. In this role, you will work on high-impact projects, leveraging cutting-edge technologies to build and maintain robust data pipelines. Collaborate with diverse multidisciplinary teams to solve complex problems and drive business value through advanced analytics. This is an excellent opportunity to grow as a technologist and leader, surrounded by inspiring individuals in a supportive environment. If you're passionate about data and technology, this role offers a chance to make a significant impact in a rapidly evolving industry.

Qualifications

• 2+ years of relevant professional experience in data engineering.
• Experience in building data pipelines for advanced analytics.
• Ability to write clean, maintainable code in Python or Scala.

Responsibilities

• Build and maintain technical platforms for advanced analytics.
• Design and build robust data pipelines for machine learning.
• Map data fields and prepare data for advanced analytics models.

Skills

Python

SQL

Data Pipeline Development

Scala

Java

Data Quality Assessment

Cloud Platforms (AWS, GCP, Azure)

Distributed Computing (Spark, Dask)

Education

Degree in Computer Science

Degree in Engineering

Degree in Mathematics

Tools

Docker

Kubernetes

Airflow

Databricks

Kedro

Job description

Data Engineer - QuantumBlack, AI by McKinsey

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Data Engineer - QuantumBlack, AI by McKinsey

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Only at McKinsey

Who You'll Work With

Only at McKinsey

Work on real-world, high-impact projects across a variety of industries – Identify micro patterns in data that our clients can exploit to maintain their competitive advantage and watch your technical solutions transform their day-to-day business.

Experience the best environment to grow as a technologist and a leader– 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.

Be surrounded by inspiring individuals as part of diverse multidisciplinary teams - Develop a holistic perspective of AI by partnering with the best design, technical, and business talent in the world as your team members.

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!

Your Impact

As a Data Engineer at QuantumBlack, 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 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.

As a Data Engineer, you’ll

• Help to build and maintain 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.
• 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.
  
  

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 (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 would be beneficial

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Consulting

• Industries

  Business Consulting and Services

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