
Data Engineer - McKinsey Digital
You will apply your passion for finding opportunities in data by using established tools and techniques, or by innovating/building new ones. You will collaborate with highly talented business consultants to design and drive architecture and implementation planning for our clients and act as a big data evangelist, educating McKinsey's and client's teams on data engineering topics. You'll do meaningful work that makes a real difference with our clients. This is a hybrid client-facing/technical role using state-of-the-art technologies, whilst also being able to communicate complex intractable ideas to non-technical audiences.
Knowledge of agile software development process and familiarity with performance metric tools
Master's degree preferred
Solid grasp of ETL across various platforms
Experienced with data modeling, design patterns, building highly scalable and secured solutions, distributed systems
Experienced on Big Data platforms and tools like AWS, Azure, GCP and tools like Spark, Kafka, Snowflake, GCS Data Proc
HTML
CSS
Python
Java
Ruby on Rails
Tableau
Perl
D3
PySpark
Time Management Skills
Azure DataFactory
Driven and self-motivated
Prioritizing skills
Adaptability
Problem Solving Skills
Detail Oriented and Organized
Verbal and Written Communication
Multi tasker
According to JobzMall, the average salary range for a Data Engineer - McKinsey Digital in 1200 19th St NW, Washington, D.C., DC 20036, USA is $78,000 to $130,000, depending on experience.
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McKinsey & Company is an American worldwide management consulting firm. McKinsey publishes the McKinsey Quarterly since 1964, funds the McKinsey Global Institute research organization, publishes reports on management topics, and has authored influential books on management.

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