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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer I - QuantumBlack, AI by McKinsey - **Company:** McKinsey & Company - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Continuous Integration, Data Architecture, Information Engineering, Data Infrastructure, Data Security, Cursor (Graphical User Interface Elements), Python (Programming Language), Machine Learning, Role-Based Access Control, Software Construction, Product Software Implementation Methods, SQL Databases, Web Application Frameworks, Google Cloud, Feature Engineering, Large Language Models, Prompt Engineering, Apache Spark, Generative AI, Information Technology, Low Latency, Dask, Machine Learning Operations, Virtual Agents, Terraform, Data Pipelines, Databricks - **Published:** June 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4da87067b7b52c98 ## About the Role Do you have experience in Software implementation?, Degree in Computer Science/Engineering, or equivalent experience 5+ years of relevant professional experience in a data engineering role, with experience leading technical workstreams, mentoring junior engineers, and driving the adoption of software engineering best practices within a team Expert-level proficiency in Python and SQL and the ability to work in polyglot environments (Scala, Java) when required by client enterprise systems Strong experience building Agentic AI, Generative AI, Machine Learning, and Business Intelligence systems, including prompt design, retrieval-augmented generation (RAG), embeddings, vector databases, context construction, and output handling in production workflows using modern frameworks (Spark, LangChain, Databricks, Dask, Airflow, Dagster, Kedro, etc.) Ability to lead the implementation of AI features end to end, with sound judgment around model behavior, evaluation, reliability, guardrails, and the trade-offs between quality, latency, and cost Experience implementing robust data security and governance controls, including managing PII/PHI, authentication, and role-based access control (RBAC) Deep knowledge of MLOps/LLMOps including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform) across cloud providers (AWS, Azure, GCP) Exceptional time management and ability to own technical workstreams autonomously Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus Strong communication skills, both verbal and written, in English and local office language(s) ## Description Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You've come to the right place. YOUR IMPACT You will be a technical owner, designing and leading the implementation of scalable data architectures for cutting-edge AI and agentic systems. You will lead the development of robust data pipelines, manage secure and governed data environments, and mentor junior colleagues while collaborating with clients and cross-functional teams. You'll tackle impactful challenges and grow as a leader by architecting innovative AI solutions across diverse industries. You will own and deliver technical workstreams, designing machine learning, agentic, and autonomous AI systems. You'll lead the integration of machine learning, Generative AI capabilities and agentic frameworks into client solutions, designing MLOps/LLMOps-focused architectures for model management, observability, and automated retraining. You will also spearhead the design of complex feature engineering workstreams, ensuring our data assets are not only robust but also optimized for the next generation of AI models. Your work will help solve some of the most complex and high-impact challenges facing clients across industries. By partnering with QuantumBlack, AI by McKinsey and QuantumBlack Labs teams, you'll lead the creation of innovative enterprise-grade machine learning systems that accelerate AI adoption and solve critical business problems at speed and scale. You will be instrumental in shaping how we build and deploy high-impact AI systems, enabling clients to achieve meaningful, lasting impact through technical innovation. You'll be based in one of our North American offices as part of our global Data Engineering community. You'll work in cross-functional Agile teams alongside Data Scientists, Machine Learning Engineers, and industry experts, leading the data engineering workstream to deliver AI solutions. Collaborating with clients from data owners to C-level executives, you'll help design impactful solutions that address complex business challenges and build client capabilities. You will grow as a technologist and a leader. You'll develop deep expertise at the intersection of technology strategy and business value by addressing diverse architectural challenges. Working with inspiring, multidisciplinary teams, you'll gain a holistic understanding of enterprise AI while collaborating with leading AI and data experts in the industry. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Architecting the Future: Leveraging AI, Cloud, and Data for Business Success](https://www.wearedevelopers.com/videos/1096-architecting-the-future-leveraging-ai-cloud-and-data-for-business-success) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Implementing Feature Environments with AWS and Terraform](https://www.wearedevelopers.com/videos/531-implementing-feature-environments-with-aws-and-terraform) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)