Big Data Engineer

SAIC is hiring a Big Data Engineer for an on-site role in Honolulu, HI, US, focused on designing, building, and maintaining real-time and near-realtime data ingestion pipelines for a mission-critical environment. The work includes moving streaming data across security domains while meeting cross-domain and data classification requirements.

What you will do

• Support continual data feeds to users and help monitor data quality and the health of overall data ingestion.
• Design, build, and maintain resilient real-time and near-realtime ingestion pipelines using Apache NiFi and REST APIs, including backpressure, prioritization, retries, and error-handling strategies.
• Configure and monitor data flows that move across security domains using cross-domain guards or solutions, ensuring data integrity and compliance with transfer policies.
• Parse, transform, validate, and route structured and unstructured data across multiple formats such as Excel, CSV, JSON, and XML.
• Use tools like Grafana and Prometheus to communicate pipeline status, data quality, and historical trends to leadership, users, and the data team.
• Collaborate with platform, software, and other data engineers to (re)configure and continuously improve ingestion pipeline reliability.
• Develop and maintain software and scripts to automate monitoring of real-time feeds and alert on timeliness, volume, lineage, and distribution data issues.
• Apply lessons learned from historical pipeline data to improve reliability and performance.
• Partner with security and governance teams to enforce requirements for encryption, authentication, authorization, and data classification across pipelines and cross-domain transfers.
• Write and maintain scripts (for example Python or Bash) to automate data processing, validation, and monitoring tasks.
• Document data flows, system configurations, and standard operating procedures.

Required qualifications

• U.S. Citizenship and an active TS/SCI clearance.
• A Bachelor of Science degree in Computer Science, Mathematics, Electrical Engineering, Physics, Information Systems, Information Technology, or a related field.
• 3+ years of experience in data engineering, data operations, or DevOps roles supporting production data pipelines.
• Proficiency in Python, Bash, or similar scripting languages used in data science and data analytics.
• Working knowledge of Linux (RedHat) command line; familiarity with Windows environments.
• Strong understanding of data engineering fundamentals including data pipelines, streaming architectures, ETL/ELT, and data quality principles.
• Familiarity with JSON, XML, CSV, and Excel data formats, parsing, and transformation.

Technologies you may work with

• Apache NiFi, REST APIs, Grafana, Prometheus
• Python, Bash, Linux (RedHat)
• Excel, CSV, JSON, XML
• Kafka, JMS
• Apache Flink, Spark Streaming
• Elasticsearch, Snowflake
• Git

Nice to have

• Experience with streaming and messaging platforms such as Kafka, JMS, Apache Flink, or Spark Streaming.
• Experience with observability tools including Elasticsearch alongside Grafana and Prometheus.
• Experience with data platforms such as Snowflake.
• Familiarity with cross-domain solutions or guards (for example data diode concepts, transfer validation, or content filtering).
• Experience enforcing encryption, authentication/authorization, and data classification policies with security and governance teams.
• Experience with version control tools like Git and Agile/Scrum practices.
• Prior experience in a government, defense, or intelligence community environment.

Location: On-site in Honolulu, HI, US. Travel: 10% of the time. Minimum clearance required: TS.SCI.

Salary range: USD 120,001 - 160,000 per year.