McKinsey & Company
Data Engineer II - QuantumBlack, AI by McKinsey
McKinsey & Company, Chicago, Illinois, United States, 60290
Digital Data Engineer II - QuantumBlack, AI by McKinsey
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 design, build, and optimize modern data platforms that power advanced analytics and AI solutions. You'll collaborate with clients and interdisciplinary teams to architect scalable pipelines, manage secure and compliant data environments, and unlock the value of complex datasets across industries. You'll sharpen your expertise by working on innovative projects, contributing to R&D, and learning from top‑tier talent in a dynamic, global environment.
By ensuring data is accurate, accessible, and production‑ready, you will enable clients to accelerate digital transformations, adopt AI responsibly, and achieve measurable business outcomes. Here are some examples of how you might contribute in a given year:
Develop a streaming data platform to integrate telemetry for predictive maintenance in aerospace systems
Implement secure data pipelines that reduce time‑to‑insight for a Fortune 500 utility company
Optimize large‑scale batch and streaming workflows for a global financial services client, cutting infrastructure costs while improving performance
Develop pipelines for embeddings and vector databases to enable retrieval‑augmented generation (RAG) for a global defense client
You will work in cross‑functional Agile teams with Data Scientists, Machine Learning Engineers, Designers, and domain experts to deliver high‑quality analytics solutions. Partnering closely with clients—from data owners to C‑level executives—you will shape data ecosystems that drive innovation and long‑term resilience.
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 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.
When you join us, you will have:
Continuous learning:
Our learning and apprenticeship culture, backed by structured programs, helps you grow in an environment where feedback is clear, actionable, and focused on your development.
A voice that matters:
From day one, we value your ideas and contributions. You will make a tangible impact by offering innovative ideas and practical solutions, and diverse perspectives 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.
World‑class benefits:
Along with 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.
Qualifications and Skills
Degree in Computer Science, Business Analytics, Engineering, Mathematics, or a 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
Hands‑on experience with cloud platforms such as AWS, GCP, Azure, Oracle, and modern data storage/warehouse solutions such as Snowflake, BigQuery, Redshift, and Delta Lake
Practical experience with Databricks, AWS Glue, and transformation frameworks like dbt, Dataform, or Databricks Asset Bundles
Knowledge of distributed systems such as Spark, Dask, Flink, and streaming platforms such as Kafka, Kinesis, Pulsar for real‑time and batch processing
Familiarity with workflow orchestration tools such as Airflow, Dagster, Prefect, CI/CD for data workflows, and infrastructure‑as‑code (Terraform, CloudFormation)
Understanding of DataOps principles including pipeline monitoring, testing, and automation, with exposure to observability tools such as Datadog, Prometheus, and Great Expectations
Exposure to ML platforms such as Databricks, SageMaker, Vertex AI, MLOps best practices, and GenAI toolkits (LangChain, LlamaIndex, Hugging Face)
Willingness to travel as required
Strong communication, time management, and resilience, with the ability to align technical solutions to business value
Equal Opportunity & Compensation FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.
Certain U.S. jurisdictions require McKinsey & Company to include a reasonable estimate of the salary for this role. For new joiners in the United States, the reasonable estimated range is
$146,600 – $150,000 USD
to help you understand what you can expect.
Additionally, we provide a comprehensive benefits package that reflects our commitment to the wellness of our colleagues and their families. This includes medical, mental health, dental and vision coverage, telemedicine services, life, accident and disability insurance, parental leave and family planning benefits, caregiving resources, a generous retirement contributions program, financial guidance, and paid time off.
FOR NON‑U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.
#J-18808-Ljbffr
Your Impact As a Data Engineer II, you will design, build, and optimize modern data platforms that power advanced analytics and AI solutions. You'll collaborate with clients and interdisciplinary teams to architect scalable pipelines, manage secure and compliant data environments, and unlock the value of complex datasets across industries. You'll sharpen your expertise by working on innovative projects, contributing to R&D, and learning from top‑tier talent in a dynamic, global environment.
By ensuring data is accurate, accessible, and production‑ready, you will enable clients to accelerate digital transformations, adopt AI responsibly, and achieve measurable business outcomes. Here are some examples of how you might contribute in a given year:
Develop a streaming data platform to integrate telemetry for predictive maintenance in aerospace systems
Implement secure data pipelines that reduce time‑to‑insight for a Fortune 500 utility company
Optimize large‑scale batch and streaming workflows for a global financial services client, cutting infrastructure costs while improving performance
Develop pipelines for embeddings and vector databases to enable retrieval‑augmented generation (RAG) for a global defense client
You will work in cross‑functional Agile teams with Data Scientists, Machine Learning Engineers, Designers, and domain experts to deliver high‑quality analytics solutions. Partnering closely with clients—from data owners to C‑level executives—you will shape data ecosystems that drive innovation and long‑term resilience.
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 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.
When you join us, you will have:
Continuous learning:
Our learning and apprenticeship culture, backed by structured programs, helps you grow in an environment where feedback is clear, actionable, and focused on your development.
A voice that matters:
From day one, we value your ideas and contributions. You will make a tangible impact by offering innovative ideas and practical solutions, and diverse perspectives 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.
World‑class benefits:
Along with 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.
Qualifications and Skills
Degree in Computer Science, Business Analytics, Engineering, Mathematics, or a 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
Hands‑on experience with cloud platforms such as AWS, GCP, Azure, Oracle, and modern data storage/warehouse solutions such as Snowflake, BigQuery, Redshift, and Delta Lake
Practical experience with Databricks, AWS Glue, and transformation frameworks like dbt, Dataform, or Databricks Asset Bundles
Knowledge of distributed systems such as Spark, Dask, Flink, and streaming platforms such as Kafka, Kinesis, Pulsar for real‑time and batch processing
Familiarity with workflow orchestration tools such as Airflow, Dagster, Prefect, CI/CD for data workflows, and infrastructure‑as‑code (Terraform, CloudFormation)
Understanding of DataOps principles including pipeline monitoring, testing, and automation, with exposure to observability tools such as Datadog, Prometheus, and Great Expectations
Exposure to ML platforms such as Databricks, SageMaker, Vertex AI, MLOps best practices, and GenAI toolkits (LangChain, LlamaIndex, Hugging Face)
Willingness to travel as required
Strong communication, time management, and resilience, with the ability to align technical solutions to business value
Equal Opportunity & Compensation FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.
Certain U.S. jurisdictions require McKinsey & Company to include a reasonable estimate of the salary for this role. For new joiners in the United States, the reasonable estimated range is
$146,600 – $150,000 USD
to help you understand what you can expect.
Additionally, we provide a comprehensive benefits package that reflects our commitment to the wellness of our colleagues and their families. This includes medical, mental health, dental and vision coverage, telemedicine services, life, accident and disability insurance, parental leave and family planning benefits, caregiving resources, a generous retirement contributions program, financial guidance, and paid time off.
FOR NON‑U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.
#J-18808-Ljbffr