Your Data Engineer expertise in Python development, including data workflows, knowledge graphs, and/or generative AI will be key to your work.
Your work will include but won't be limited to creation of the python code, tests, creation and modification of GitHub Action CICD pipelines, working with AWS-based infrastructure, and docker containers.
As an Forward Deployed Engineer (FDE) Data Engineer, you are critical for upcoming deployments, as you will combine software and data engineering skills, bring data science literary to collaborate effectively and focus on platform engineering: deploying, debugging, and running systems.
In this role, you will focus on delivering and scaling AI solutions by embedding yourself into cross-functional teams of clients or consultants to drive measurable business value. You will deploy assets on client service teams (CSTs) and later return to refine and enhance these assets, ensuring they are optimized for broader use. Working alongside a team of data engineers, software engineers, and data scientists, you will develop robust data ingestion pipelines and mature data processing capabilities that feed into data systems supporting generative AI applications. Your work will involve creating Python code, writing tests, modifying and managing GitHub Action CI/CD pipelines, and working with AWS-based infrastructure and Docker containers to ensure seamless integration and deployment.
Your responsibilities will include deploying solutions across McKinsey, client, and third-party cloud environments such as AWS, Azure, and GCP. You will troubleshoot, analyze, and resolve technical issues, ensuring that all fixes align with the overarching product strategy and are integrated into the master code base. Additionally, you will develop and support customizations and extensions tailored to client-specific needs, providing technical guidance on deployment, configuration, and issue resolution.
Beyond deployment, you will contribute to improving pipelines, tooling, and engineering standards, ensuring the platform remains cutting-edge and efficient. When not actively engaged in deployments, you will support ongoing product development, helping to shape the platform’s future capabilities and impact.