Data Engineer, Lead

Design and deliver enterprise data foundations that enable AI applications to use authorized information.

Responsibilities

• Design enterprise data architectures and build pipelines, knowledge indexes, and retrieval services that ground agents in authorized enterprise information
• Partner with source-system owners and engineering teams to define data contracts
• Integrate structured and unstructured sources while maintaining permissions, lineage, quality, and freshness
• Own reliability of data and retrieval services
• Collaborate with AI Engineering on retrieval behavior and response quality
• Support ingestion, transformation, indexing, synchronization, and retrieval service implementation and maintenance
• Align engineering execution with role emphasis: architecture and governance decisions (architect) and pipeline, connector, and service implementation (engineer)

Requirements

• Experience designing or implementing enterprise data platforms, lakehouse architectures, and integrations for structured and unstructured data
• SQL and Python experience, including developing, testing, and operating ETL or ELT pipelines
• Experience defining data models, schemas, data contracts, APIs, and access patterns for downstream applications
• Experience with data governance including source permissions, lineage, quality controls, and monitoring for freshness and availability
• Knowledge of retrieval-augmented generation, embeddings, vector indexes, and semantic or hybrid search
• Ability to troubleshoot ingestion and retrieval failures and assess relevance, latency, scalability, and data quality
• Ability to translate enterprise requirements into architecture decisions, integration standards, and governance patterns
• Ability to implement and maintain ingestion, transformation, indexing, synchronization, and retrieval services
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
• Bachelor’s degree

Technologies

• SQL
• Python
• ETL
• ELT

Nice If You Have

• Experience with Databricks, Spark, Delta Lake, vector databases, or comparable platforms
• Experience with permission-aware retrieval, metadata enrichment, incremental ingestion, or knowledge engineering
• Experience delivering reusable customer connectors and data services for production AI applications

Benefits

• Health, life, disability, financial, and retirement benefits
• Paid leave
• Professional development
• Tuition assistance
• Work-life programs
• Dependent care
• Recognition awards program

Vetting

• Selected applicants will be subject to a government investigation
• Eligibility requirements may apply for the U.S. government client

Compensation

• Projected compensation range: $77,600.00 to $176,000.00 (annualized USD)

Work Model

• Onsite: work will primarily be performed full-time at a customer facility in McLean, VA

Identity Statement

• Applicants are expected to be on camera during interviews and assessments
• Booz Allen reserves the right to take a picture to verify identity and prevent fraud

Candidate AI Usage Policy

• Use of artificial intelligence (AI) or other tools to assist with responses during interviews is prohibited unless permission is explicitly provided

Commitment to Non-Discrimination

• All qualified applicants will receive consideration without regard to disability, protected veteran status, or any other status protected by applicable law