Data Engineer II Critical Industries

Position: Data Engineer II - Quantum Black, AI by McKinsey (Critical Industries)
Location: New York

Job Summary
:
Quantum Black, AI by McKinsey is focused on driving lasting impact and building long-term capabilities for clients. As a Data Engineer II, you will design, build, and optimize data platforms that power advanced analytics and AI solutions while collaborating with interdisciplinary teams to manage secure data environments and unlock the value of complex datasets.

Responsibilities
:

• 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.

Qualifications
:
Required
:

• 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 Py Spark

• Hands-on experience with cloud platforms such as (AWS, GCP, Azure, Oracle) and modern data storage/warehouse solutions such as Snowflake, Big Query, 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 (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, Cloud Formation)

• Understanding of Data Ops 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, Sage Maker, Vertex AI), MLOps best practices, and GenAI toolkits (Lang Chain, Llama Index, Hugging Face)

• Willingness to travel as required

• Strong communication, time management, and resilience, with the ability to align technical solutions to business value

Company
:
We are Quantum Black, AI by McKinsey. Founded in 2009, the company is headquartered in London, G , with a team of  employees. The company is currently Late Stage.