Databricks Lakehouse Engineer for Fraud Analytics

Booz Allen Hamilton; McLean (VA); On-site; USD 78,000 - 176,000; Full time

Job summary

Booz Allen Hamilton is seeking a Databricks Lakehouse Engineer and Analyst, Mid, to unlock insights from complex data in federal environments in McLean, VA. You will contribute across data engineering, analytics engineering, and model integration, partnering with fraud analytics teams and stakeholders.

This role emphasizes Databricks, Delta Lake, PySpark, and ML/NLP techniques to deliver real-time risk insights while collaborating in a fast-paced, mission-driven setting.

Qualifications

• 3+ years of experience in data engineering, analytics engineering, or ML engineering.
• Experience with Databricks, Delta Lake, and PySpark.
• Experience with structured streaming and medallion architecture.
• Experience supporting fraud analytics, risk scoring, or anomaly detection.
• Experience working independently in a fast-moving, high-impact environment.
• Knowledge of Unity Catalog governance and access controls, and text mining or ML techniques.
• Knowledge of ML, AI, or Natural Language Processing (NLP).
• Ability to collaborate with fraud operations and technical stakeholders.
• Secret clearance
• Bachelor’s degree

Responsibilities

• Contribute across data engineering, platform configuration, fraud analytics enablement, and stakeholder coordination.
• Collaborate with data scientists and fraud operations to deliver analytics capabilities.
• Implement and govern data pipelines and AI-enabled risk insights.

Skills

Data engineering

Analytics engineering

ML engineering

Databricks

Delta Lake

PySpark

Structured streaming

Unity Catalog governance

ML / NLP

NLP

Education

Bachelor’s degree

Master’s degree

Tools

Databricks

Delta Lake

PySpark

MapReduce

Hadoop

Hive

EMR

Kafka

Spark

Gurobi

MySQL

Job description

Booz Allen Hamilton is seeking a Databricks Lakehouse Engineer and Analyst, Mid, to unlock insights from complex data in federal environments in McLean, VA. You will contribute across data engineering, analytics engineering, and model integration, partnering with fraud analytics teams and stakeholders.

This role emphasizes Databricks, Delta Lake, PySpark, and ML/NLP techniques to deliver real-time risk insights while collaborating in a fast-paced, mission-driven setting.