Realtime Data Analytics Engineer

Booz Allen Hamilton•Beavercreek, OH

15d•$77,500 - $176,000•Hybrid

About The Position

Are you looking for an opportunity not just to analyze data, but to architect real-time analytics platforms that deliver critical insights in the defense industry? As a Realtime Data Analytics Engineer, you’ll drive end-to-end product design, from ingestion to computation to visualization for low-latency, high-volume data pipelines. Using agile lifecycle development and Git-based workflows, you’ll partner with engineers, architects, and data scientists to operationalize streaming analytics, embed models into production systems, and deliver insights where milliseconds matter. As a data engineer at Booz Allen, you’ll help build advanced technology solutions and implement data engineering activities on some of the most mission-driven projects in the industry. You’ll deploy and develop pipelines and platforms that organize and make disparate data meaningful. Here, you’ll work with a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll use your experience in analytical exploration and data examinations while you manage the assessment, design, building, and maintenance of scalable platforms for your clients.

Requirements

5+ years of experience in data engineering, analytics engineering, or streaming-focused software development
Experience with Python, SQL, and a streaming framework such as Flink, Spark Streaming, Kafka Streams, or ksqlDB
Experience with relational data stores such as PostgreSQL or SQL Server, and NoSQL platforms such as MongoDB or DynamoDB
Knowledge of building and exposing analytics through REST APIs, WebSockets, and front-end technologies
Ability to work with Docker and Kubernetes for scalable analytics deployments
Ability to travel up to 25% of the time
Secret clearance
Bachelor’s degree

Nice To Haves

Experience with real-time feature stores, Delta Lake, Apache Iceberg, or other large-scale data lake technologies
Experience with advanced observability, anomaly detection, or model monitoring
Experience integrating analytics with game engines, such as Unity, Unreal, or Prepar3D, for spatial or simulation-driven visualization
Experience with data warehousing using AWS Redshift, MySQL, or Snowflake
Experience with Agile engineering practices
Top Secret clearance

Responsibilities

Architect and optimize streaming analytics pipelines using Kafka, Flink, Spark Streaming, or Kafka Streams, including windowing, stateful processing, and exactly-once semantics.
Build and refine data models, feature extraction patterns, and timeseries analytics for largescale, high-velocity data.
Design and deploy real-time APIs and visualization layers using REST, WebSockets, and modern UI frameworks.
Integrate operational machine learning workflows, including online inference, drift monitoring, and performance tuning.
Implement observability for analytics workloads, including metrics, tracing, and instrumentation for data quality and latency.
Utilize Docker and Kubernetes to deploy analytics services across cloud environments such as AWS and Azure.
Establish best practices for data governance, schema evolution, lineage, and auditability across streaming ecosystems.
Mentor engineers and data scientists, review designs and code, and champion SDLC best practices, testing, and documentation.