YOUR IMPACT

You will partner with global teams to design, deliver, and deploy differentiated advanced analytics and agentic solutions that address high-value commercial use cases across the Life Sciences sector.

You will help transform standalone pilots into integrated, production-ready systems that reshape end-to-end commercial workflows and drive meaningful impact for patients.

You will design and manage scalable data pipelines and secure analytics platforms, lead technical initiatives, and mentor team members while contributing to innovative R&D projects. Collaborating with diverse Agile teams, you'll leverage cutting-edge technologies to create impactful solutions that support McKinsey's asset-based consulting model and help clients harness the full potential of their data.

You will own the technical platform for advanced analytics solutions, designing and building scalable, modular, and reproducible data pipelines for machine learning and full-stack agentic applications. You will manage secure data environments, map data fields to hypotheses, and prepare data for advanced models and agentic reasoning. Additionally, you will lead technical workstreams, mentor junior colleagues, and contribute to R&D projects and internal asset development.

Your work will have a real-world impact by building technology assets for internal and external clients; you will help organizations address critical challenges and support McKinsey's shift toward asset-based consulting. Your contributions will enable scalable, repeatable solutions that deliver lasting value.

You will work in Agile teams alongside data scientists, machine learning engineers, and industry experts to develop impactful analytics solutions that help clients unlock the full potential of their data.

You'll have the freedom to innovate and grow. You'll work with leading technologies, collaborate with diverse teams, and partner with top talent in design, technology, and business. Your work offers a unique opportunity to gain a holistic perspective on AI and data engineering while driving innovation.

You'll be working in one of our North American offices in our Life Sciences practice. You will help revolutionize how Pharma and MedTech companies connect with their customers to improve human lives. You will be working in a team that is fully integrated with QuantumBlack, AI by McKinsey.

There is flexibility to hire at the Senior Data Engineer I/II or Principal Data Engineer I/II level, depending on your experience.

YOUR QUALIFICATIONS AND SKILLS

• Degree in computer science, business analytics, engineering, mathematics, or a related field
• 5+ years of professional experience in data engineering, software engineering, or adjacent technical roles
• Proficiency in Python for production-grade pipelines, with strong skills in SQL and PySpark
• Proven experience building end-to-end data pipelines and platforms for Agentic AI, Generative AI, Machine Learning, or Business Intelligence, covering data preparation, embeddings generation, vector search, and system integration using modern frameworks (Pandas, Spark, dbt, LangChain, LangGraph).
• Familiarity with workflow orchestration tools such as Temporal, CI/CD for data workflows, and infrastructure-as-code (Terraform, CloudFormation)
• Familiarity with vector databases and understanding of low latency serving patterns is a plus
• Experience building systems with different data formats (structured vs unstructured) and data processing methods (streaming vs batch) and deploying across major cloud platforms (AWS, Azure, GCP)
• A strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Databricks Asset Bundles, Snowflake, BigQuery, PSQL, etc.)
• Understanding of MLOps and LLMOps principles including pipeline monitoring, testing, and evals, with exposure to observability tools such as Langfuse, LangSmith, and Opik
• Strong communication skills, both verbal and written, in English, with the ability to adjust your style to suit different perspectives and seniority levels.

Please review the additional requirements regarding essential job functions of McKinsey colleagues.

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