Data Engineer - QuantumBlack
McKinsey & Company
Data Engineer - QuantumBlack
Who You'll Work With
You will join our Stockholm office as part of QuantumBlack. You will work with other data engineers, data scientists, designers and strategy consultants on interdisciplinary projects.
You'll work hands in hands with our clients, from data owners and users to C-level executives.
What You'll Do
As a data engineer at QuantumBlack, you will work in multi-disciplinary environments harnessing data to provide real-world impact for organisations globally. You will influence many of the recommendations our clients need to positively change their businesses and enhance performance.
- Partner with our clients, from data owners and users to C-level executives, to understand their needs and build impactful analytics solutions
- Design and build data pipelines to support data science projects following software engineering best practices
- Use state of the art technologies to acquire, ingest and transform big datasets
- Map data fields to hypothesis, curate, wrangle and prepare data to be used in advanced analytics models
- Create and manage data environments in the cloud or on premise
- Ensure information security standards are maintained at all time
- Contribute to cross-functional problem-solving sessions with your team and deliver presentations to colleagues and clients
- Be flexible to travel to our clients' offices to deliver presentations, gather information or share knowledge
Our tech stack
While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, SQL, Airflow, Databricks, Kedro (an OSS developed by QuantumBlack), container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP or Azure, and more!
- Degree educated in computer science, engineering, mathematics or related field
- Ability to write clean, maintainable and robust code in Python and SQL; familiarity with Java and Scala is a plus
- Knowledge of software engineering concepts and best practices
- Familiarity with the latest OSS, cloud, container, query and database technologies as well as query languages
- Experience with big data tools such as Hadoop, Spark, Kafka, Hive is a plus
- Previous commercial experience in a data-driven role
- Confirmed experience building data pipelines in production and ability to work across structured, semi-structured and unstructured data
- Experience preparing data for analytics and following a data science workflow
- Commercial client-facing or senior stakeholders management experience is a plus
- Business level fluency in the local language and English (verbal and written)
FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.
FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.