Data Engineer II - QuantumBlack, AI by McKinsey (Critical Industries)

McKinsey & Company; Newark (NJ); On-site; USD 80,000 - 120,000; Full time

Benefits offered by this job

World-class benefits

Mentorship opportunities

Continuous learning environment

Job summary

McKinsey & Company in Newark is seeking a Data Engineer II who will design and optimize modern data platforms that enable advanced analytics and AI solutions. You'll collaborate with interdisciplinary teams to build scalable pipelines and manage secure data environments, driving significant impact across various industries.

The ideal candidate will have a degree in a related field, proficiency in programming languages like Python and SQL, and experience with cloud platforms. This position offers substantial growth opportunities and the chance to work in a dynamic global environment.

Qualifications

• 2+ years of professional experience in data engineering or related technical roles.
• Hands-on experience with cloud platforms and data storage solutions.
• Familiarity with workflow orchestration tools and DataOps principles.

Responsibilities

• Design and optimize data platforms for advanced analytics.
• Collaborate with teams to manage secure data environments.
• Develop streaming data platforms for predictive maintenance.

Skills

Proficient in Python

SQL skills

Experience with cloud platforms

Knowledge of distributed systems

Strong communication abilities

Education

Degree in Computer Science, Business Analytics, Engineering, or related field

Tools

AWS

GCP

Databricks

Airflow

Terraform

Job 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

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.

Your work will drive lasting impact. By ensuring data is accurate, accessible, and production‑ready, you’ll enable clients to accelerate digital transformations, adopt AI responsibly, and achieve measurable business outcomes.

• 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’ll 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’ll shape data ecosystems that drive innovation and long‑term resilience.

In addition to critical industries such as Government, Defense, Aerospace, Utilities, Oil and Gas, you will also have the ability to serve other industries.

YOUR GROWTH

We foster a high‑performance culture that rewards determination, curiosity, and resilience. In return for your drive, we provide resources, mentorship, and opportunities that accelerate your development into a stronger leader.

You will experience continuous learning, a voice that matters, a global community, and world‑class benefits in a structured, feedback‑rich environment.

YOUR QUALIFICATIONS AND SKILLS

• U.S. Citizenship is required for this role (you must be able to be staffed on Critical Industries work which includes Government, Defense, Aerospace, Utilities, etc.)
• 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
• 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

FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action 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.

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.