Senior Data Engineer - QuantumBlack, AI by McKinsey

Who You'll Work With

You will be based in our Riyadh, Saudi Arabia or Cairo, Egypt office as part
of our QuantumBlack, AI by McKinsey team, partnering with consultants,
clients, and other colleagues.
Our QuantumBlack, AI by McKinsey teams bring the latest analytical techniques
plus a deep understanding of industry dynamics and corporate functions to help
clients create the most value from data.

What You'll Do

You will apply your passion for finding opportunities in data by using
established tools and techniques or by innovating/building new ones.
In this role, you will collaborate with highly talented business consultants
and data-scientists 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 actively
cooperate with data scientists and digital consultants to incorporate clients'
requirements and impactful analysis into our data products. You'll also be an
expert in data engineering and advise relevant people at the firm on technical
aspects of analytics engagements.
You will shape the future of what data-driven organizations look like, drive
processes for extracting and using that data in creative ways, and create new
lines of thinking within an infinite number of clients and situations.
Lastly, 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.

Qualifications

• Bachelor's degree in computer science, engineering, mathematics or another relevant subject


• ‎3+ years of experience in big data related software development; experience with data modeling, design patterns and building highly scalable and secured solutions


• Background in development with practical experience with at least one general purpose programming languages (Python, R, C, Java, Scala, etc.)


• Familiar with big data platforms (SQL, Teradata, Hadoop, Spark)


• Experience preparing data for analytics and following a data science workflow


• Advanced knowledge of data structures and algorithms, networking, operating systems, standard unix/linux operating systems, version control and DevSecOps tool chains, etc.


• Ability to work with a myriad of data types (structured and unstructured), extracting information from modern and legacy data platforms and identify and perform linkages across disparate data sets


• Meaningful experience in extracting and loading data from multiple database technologies like RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL), MPP (AWS Redshift, Teradata, Snowflake) and optionally NoSQL (MongoDB, DynamoDB, Cassandra, Neo4J, Titan)


• Experience and interest in Cloud platforms such as AWS, Azure, GCP


• Commercial client-facing project experience is helpful


• Proven record of leadership in a work setting and/or through extracurricular activities


• Ability to work collaboratively in a team environment and effectively with people at all levels in an organization


• Ability to communicate complex ideas effectively, both verbally and in writing, in English; fluency in local office language(s) is a plus