Data Engineer

Booz Allen Hamilton

The Opportunity

Make enterprise data and knowledge usable, governed, and dependable for AI applications.

Design data architectures and build the pipelines, knowledge indexes, and retrieval services that ground agents in authorized enterprise information.

Work with source-system owners and engineering teams to define data contracts, integrate structured and unstructured sources, and maintain permissions, lineage, quality, and freshness.

Own the reliability of data and retrieval services while partnering with AI Engineering on application retrieval behavior and response quality.

Architect positions emphasize architecture and governance decisions.

Engineer positions emphasize pipeline, connector, and service implementation.

Key Responsibilities

• Implement and maintain ingestion, transformation, indexing, synchronization, and retrieval services.
• Troubleshoot ingestion and retrieval failures and assess relevance, latency, scalability, and data quality.
• Translate enterprise requirements into architecture decisions, integration standards, and governance patterns.

Requirements & Tech Stack

• SQL and Python
• Developing, testing, and operating ETL or ELT pipelines
• Defining data models, schemas, data contracts, APIs, and access patterns that support downstream applications
• Data governance, source permissions, lineage, quality controls, and monitoring for freshness and availability
• Retrieval-augmented generation, embeddings, vector indexes, and semantic or hybrid search

Qualifications

• Experience designing or implementing enterprise data platforms, lakehouse architectures, and integrations for structured and unstructured data.
• Experience with data governance, source permissions, lineage, quality controls, and monitoring for freshness and availability.
• 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

Nice To 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.

Additional Information

• U.S. citizenship is required.
• Identity verification process will be utilized, requiring you to be on camera during interviews and assessments.
• The use of AI or other tools to assist with responses during interviews is prohibited unless explicitly permitted.
• Work Model: Remote, Hybrid, or Onsite (details may vary based on listing).