Databricks Lakehouse Engineer & Analyst, Senior

As a data scientist, you’re excited at the prospect of unlocking the secrets held by a data set, and you’re fascinated by the possibilities presented by IoT, machine learning, and artificial intelligence. In an increasingly connected world, massive amounts of structured and unstructured data open new opportunities. As a data scientist at Booz Allen, you can help turn these complex data sets into useful information to solve global challenges. Across private and public sectors—from fraud detection to cancer research to national intelligence—we need you to help find the answers in the data.

Our U.S. government agency client is standing up a next-generation Databricks Lakehouse environment to power real-time fraud detection, investigative decisioning, and AI-driven risk modeling. We are seeking an exceptional, hands-on technical leader who can own the full architecture end-to-end while also guiding functional analysis, model integration, governance, and delivery in a complex federal environment. This mid-level role blends responsibilities typically spread across a Data Engineer, Platform Architect, ML Engineer, Business Analyst, and Federal Program Manager. The ideal candidate is a versatile Databricks practitioner who excels at building scalable data systems, enabling fraud operations, and ensuring compliance in a regulated federal context.

Responsibilities

• Design and implement end-to-end Databricks Lakehouse architecture for real-time fraud detection, investigative decisioning, and AI-driven risk modeling
• Develop and maintain Bronze, Silver, and Gold data architectures using Databricks, Delta Lake, PySpark, and structured streaming
• Lead fraud analytics, anomaly detection, and risk scoring initiatives
• Implement Unity Catalog governance in a regulated federal environment
• Collaborate with federal stakeholders to ensure compliance and alignment with mission objectives
• Operate independently in a lean, high-impact environment while guiding cross-functional teams

Requirements

• 5+ years of experience with data engineering, architecture, or ML engineering
• Hands-on experience with Databricks, Delta Lake, PySpark, and structured streaming
• Experience designing Bronze, Silver, or Gold architectures
• Experience with fraud analytics, anomaly detection, or risk scoring
• Knowledge of Unity Catalog governance
• Ability to collaborate with federal stakeholders in a regulated environment
• Public Trust clearance required
• Bachelor’s degree

Preferred Qualifications

• Experience developing algorithms using R, Python, or SQL/NoSQL
• Experience with distributed data and computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, MySQL)
• Experience with visualization packages (Plotly, Seaborn, ggplot2)
• Exceptional cross-functional communication skills for both technical and non-technical audiences

Benefits

• Health, life, disability, and retirement benefits
• Paid leave, professional development, and tuition assistance
• Work-life programs and dependent care support
• Recognition awards program for exceptional performance and demonstration of company values

Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet this threshold are only eligible for select offerings, not inclusive of health benefits.

Pay

The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). Salary is determined by various factors, including location, education, skills, competencies, experience, and contract-specific affordability and organizational requirements.

Schedule

This role may be remote, hybrid, or onsite:

• Remote: Primarily virtual, with occasional in-person work at a Booz Allen or customer facility
• Hybrid: Frequent work from a Booz Allen facility, with potential visits to customer sites as needed
• Onsite: Work primarily performed at a Booz Allen office or customer facility, with direct collaboration required

Employees working virtually are generally expected to have their cameras on during meetings to support engagement and effective communication.