Big Data Engineer

SAIC is hiring a Big Data Engineer for an on-site role in Honolulu, HI. The position focuses on designing, building, and maintaining real-time and near-real-time data ingestion pipelines for a mission-critical environment, including the secure movement of streaming data across security domains.

Responsibilities

• Support the delivery of continual data feeds to users and monitor data quality and end-to-end ingest performance.
• Design, build, and maintain resilient real-time and near-real-time 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 guard solutions, ensuring data integrity and alignment with transfer policies.
• Parse, transform, validate, and route structured and unstructured data across formats including Excel, CSV, JSON, and XML.
• Use data manipulation and visualization tools such as Grafana and Prometheus to communicate pipeline health, data quality, and historical trends.
• Collaborate with platform, software, and other data engineering teams to (re)configure and continuously improve ingestion reliability.
• Develop and maintain software and scripts to automate monitoring of real-time feeds and alert on issues related to timeliness, volume, lineage, and distribution.
• Apply insights from historical pipeline behavior to improve data ingest reliability and performance.
• Partner with security and governance teams to enforce encryption, authentication, authorization, and data classification requirements for pipelines and cross-domain transfers.
• Write and maintain scripts (such as Python and Bash) to automate data processing, validation, and monitoring tasks.
• Document data flows, system configurations, and standard operating procedures.

Requirements

• U.S. Citizenship and active TS/SCI clearance.
• 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 environments; familiarity with Windows environments.
• Strong understanding of data engineering fundamentals, including data pipelines, streaming architectures, ETL/ELT concepts, and data quality principles.
• Familiarity with JSON, XML, CSV, and Excel data formats, including parsing and transformation.

Technologies

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

Preferred Qualifications

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

Location and Clearance

Location: Honolulu, HI, US (onsite).
Travel: Yes, 10% of the time.
Minimum clearance required: TS.SCI.
Clearance level must be able to obtain: None.

Compensation

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