Data Engineer

Job description

• Working alongside Oliver Wyman consulting teams and partners, engaging directly with clients to understand their business challenges
• Exploring large-scale data and designing, developing, and maintaining data/software pipelines, and ETL processes for internal and external stakeholders
• Explaining, refining, and developing the necessary architecture to guide stakeholders through the journey of model building
• Advocating application of best practices in data engineering, code hygiene, and code reviews
• Leading the development of proprietary data engineering, assets, ML algorithms, and analytical tools on varied projects
• Creating and maintaining documentation to support stakeholders and runbooks for operational excellence
• Working with partners and principals to shape proposals that showcase our data engineering and analytics capabilities
• Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them
• Keeping up with emerging state-of-the-art data engineering techniques in your domain

Your Attributes, Experience Qualifications

• Bachelors or master s degree in a computational or quantitative discipline from a top academic program (Computer Science, Informatics, Data Science, or related)
• Exposure to building cloud ready applications
• Exposure to test-driven development and integration
• Pragmatic and methodical approach to solutions and delivery with a focus on impact
• Independent worker with ability to manage workload and meet deadlines in a fast-paced environment
• Collaborative team player
• Excellent verbal and written communication skills and command of English
• Willingness to travel
• Respect for confidentiality

Technical Background

• Prior experience in designing and deploying large-scale technical solutions
• Fluency in modern programming languages (Python is mandatory; R, SAS desired)
• Experience with AWS/Azure/Google Cloud, including familiarity with services such as S3, EC2, Lambda, Glue
• Strong SQL skills and experience with relational databases such as MySQL, PostgreSQL, or Oracle
• Experience with big data tools like Hadoop, Spark, Kafka
• Demonstrated knowledge of data structures and algorithms
• Familiarity with version control systems like GitHub or Bitbucket
• Familiarity with modern storage and computational frameworks
• Basic understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
• Valued but not required:
• Compelling side projects or contributions to the Open-Source community
• Prior experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet)
• Familiarity with containerization technologies, such as Docker and Kubernetes
• Experience with UI development using frameworks such as Angular, VUE, or React
• Experience with NoSQL databases such as MongoDB or Cassandra
• Experience presenting at data science conferences and connections within the data science community