Databricks Lakehouse Engineer and Analyst, Mid

Booz Allen Hamilton•McLean, VA

7d•$77,600 - $176,000

About The Position

Our U.S. government agency client is building a modern Databricks Lakehouse environment to support real‑time fraud detection, investigative analytics, and AI‑driven risk insights. We are seeking a hands‑on, versatile Databricks engineer who can contribute across data engineering, functional analysis, governance, and model integration in a federal environment. This role combines responsibilities across data engineering, platform configuration, fraud analytics enablement, and stakeholder coordination. Work with us as we use data science for good. Join us. The world can’t wait.

Requirements

4+ 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

Nice To Haves

3+ years of experience in the development of algorithms leveraging R, Python, SQL, or NoSQL
3+ years of experience with distributed data or computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL
2+ years of experience with ML, AI, or NLP
Experience with visualization packages, including Plotly, Seaborn, or ggplot2
Possession of strong communication skills, for both technical and non‑technical audiences
Possession of strong problem-solving skills
Master’s degree

Responsibilities

Contribute across data engineering, functional analysis, governance, and model integration in a federal environment.
Combine responsibilities across data engineering, platform configuration, fraud analytics enablement, and stakeholder coordination.