Job Number: R0245465 Realtime Data Analytics Engineer The Opportunity: 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. What You'll Do: - 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. Join us. The world can't wait. You Have: - 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 If You Have: - 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 Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Secret clearance is required.