Data Engineer II - McKinsey Digital

McKinsey & Company • Atlanta, Georgia, United States • 2h ago

Job ID: 103414

AtlantaBostonCharlotteChicagoDallasNew Jersey

+ 6 More

Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

YOUR IMPACT

As a Data Engineer II, you will play a pivotal role in designing, building, and optimizing modern data architectures that power cutting-edge Agentic and AI-driven solutions.

Your work will unlock the full potential of data across industries, enabling teams to operate, innovate, and excel at the level of leading technology companies.

Our technology, data, and AI practice areas include Strategy & Performance, Talent & Operating Model, Technology Modernization, and Data Transformation. Leveraging McKinsey’s structured DRIVE framework, the Data Acceleration Lab, and an ecosystem of over 50 proprietary assets, you will help deliver rapid, impactful, and large-scale data transformations, turning data into a strategic business asset for our clients.

While part of a global, multinational organization, our teams are diverse and small, operating with the agility and culture of a startup to deliver tailored solutions quickly and effectively. Our office culture is casual, fun, and social, with a strong emphasis on continuous learning and innovation. You’ll have the freedom to experiment with new ideas, be creative, and grow your expertise.

You will design and build high-quality data products that drive scalable data platforms and power advanced AI and agentic systems. Working closely with our engineering, product, and technology teams, you will play a key role in accelerating impact. Additionally, you will contribute to enhancing McKinsey’s data transformation assets, accelerators, and reference architectures.

Here’s how you might contribute in a given year:

You will design, develop, and maintain scalable and efficient data pipelines to support modern data architecture and AI-driven solutions that demand real-time or streaming data. Collaborating with senior engineers to implement and optimize Agentic GenAI capabilities within data workflows and data products (e.g., Embedding, Prompt and Context engineering, RAG).

You will secure data storage, retrieve, and process data to ensure data privacy and controls (e.g., Role-based access, Encryption options). You will also analyze and optimize data storage, retrieve, and process (i.e., batch and real-time) to ensure high performance and reliability.

You will address complex data challenges, including data integration, transformation, and quality assurance, using modern AI and GenAI-powered tools.

You will collaborate with some of the best technical (e.g., data scientists, software engineers, ML engineers) and business talent (e.g., domain experts) in an Agile team setting to align data engineering efforts with business and technical goals.

You will adhere to data engineering best practices, including coding standards, data governance, and security protocols.

You will maintain clear and comprehensive documentation for data pipelines, workflows, and data architecture.

YOUR GROWTH

Driving 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.

YOUR QUALIFICATIONS AND SKILLS

Degree in Computer Science, Business Analytics, Engineering, Mathematics, or related field
2+ years of professional experience in data engineering, software engineering, or adjacent technical roles
Proficiency in Python, Scala, or Java for production-grade pipelines, with strong skills in SQL and PySpark. Familiarity with commercial platforms (e.g., Informatica, Talend) is a plus
Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure, Oracle) and modern data storage/warehouse solutions (e.g., Snowflake, BigQuery, Redshift, Delta Lake)
Practical experience with Databricks, Azure Data Factory, AWS Glue, and transformation frameworks like dbt, Dataform, or Databricks Asset Bundles
Knowledge of data modeling, design patterns, distributed systems (e.g., Spark, Dask, Flink), and streaming platforms (e.g., Kafka, Kinesis, Pulsar) for real-time and batch processing
Familiarity with workflow orchestration tools (e.g., Airflow, Dagster, Prefect), CI/CD for data workflows, and infrastructure-as-code (e.g., Terraform, CloudFormation)
Understanding of DataOps principles, including CI/CD pipeline, monitoring, testing, and automation, with exposure to observability tools (e.g., Datadog, Prometheus, Great Expectations); familiarity with MLOps best practices is a plus
Familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS, pgvector), BI tools (e.g., Power BI), GenAI toolkits (e.g., LangChain, LlamaIndex, Hugging Face), and embeddings pipelines for GenAI and semantic search applications is a plus
Understanding of low latency serving patterns (i.e., caching, batching, quantization) and awareness of Responsible AI principles, including bias and hallucination monitoring, is a plus
Strong communication, time management, and resilience, with the ability to align technical solutions to business value
Willingness to travel as required

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