Senior Data Engineer - Life Sciences.AI

Job ID: 111449Type of role: Full-timeInterest: Serve Clients / Tech & AISkill group: N/AIndustries: High Tech, Life SciencesRegion: North AmericaLocations: Atlanta (United States) | Boston (United States) | Charlotte (United States) | Connecticut - Darien (United States) | Miami (United States) | New Jersey (United States) | New York (United States) | Philadelphia (United States) | Raleigh (United States) | Washington DC (United States)Compensation Range: $176,000 - $179,500Posted (LinkedIn): 2026-09-11Created: 2026-08-20Apply: 'll be on the global Life Sciences AI team, fully integrated with QuantumBlack, AI by McKinsey, as a senior software engineer, building AI that transforms Pharma and MedTech.Who you'll work withDriving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.What you'll doYou 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 backgroundDegree in computer science, business analytics, engineering, mathematics, or a related field5+ 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.