Data Engineer II - QuantumBlack, AI by McKinsey (Critical Industries)
Who You'll Work With
- 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 Do
- 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.
Your Background
- 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 (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