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oracle

Big Data Engineer

SAIC
Honolulu, USA
Mid · 3+ years experience
Onsite
Discovered 1 weeks ago
bashelasticsearchflinkgitgrafanakafka

Full Job Posting

Qualifications

  • TYPICAL EDUCATION AND EXPERIENCE: Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience; PhD or JD and four (4) years or more experience.
  • U.S. Citizenship and an active TS/SCI clearance.
  • Bachelor of Science degree in Computer Science, Mathematics, Electrical Engineering, Physics, Information Systems, Information Technology, or 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 commonly used in data science/data analytics applications.
  • Working knowledge of the Linux (RedHat) command line; familiarity with Windows environments.
  • Solid understanding of data engineering fundamentals: data pipelines, streaming architectures, ETL/ELT concepts, and data quality principles.
  • Familiarity with JSON, XML, CSV, and Excel data formats, parsing, and transformation.
  • Preferred Qualifications (Nice to Have)
  • Experience with streaming/messaging platforms and tools: Kafka, JMS, Apache Flink/Spark Streaming.
  • Experience with monitoring/observability tools: Grafana, Prometheus, Elasticsearch.
  • Experience with data platforms such as Snowflake.
  • Familiarity with cross domain solutions/guards (e.g., data diode concepts, transfer validation, content filtering).
  • Experience enforcing encryption, authentication/authorization, and data classification policies in partnership with security/governance teams.
  • Experience with version control tools (e.g., Git) and Agile/Scrum practices.
  • Prior experience in a government, defense, or intelligence community environment.

Preferred Qualifications

  • Preferred Qualifications (Nice to Have)

Responsibilities

  • Aid the team in delivering continual data feeds to users and monitoring the health of data quality and overall data ingest.
  • Design, build, and maintain resilient real-time/near-realtime ingestion pipelines using Apache NiFi and REST APIs, with appropriate backpressure, prioritization, retries, and error-handling strategies.
  • Configure and monitor data flows moving across security domains via cross domain guards/solutions, ensuring data integrity and compliance with transfer policies.
  • Parse, transform, validate, and route structured and unstructured data in a variety of formats, including Excel, CSV, JSON, and XML.
  • Employ data manipulation and visualization tools (e.g., Grafana, Prometheus) to effectively convey 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 data ingestion pipeline reliability.
  • Develop and maintain software/scripts to automate monitoring of real-time feeds and alert on timeliness, volume, lineage, and distribution data issues.
  • Translate learnings from historical pipeline data into actionable steps to improve data ingest reliability and performance.
  • Partner with security and governance teams to enforce encryption, authentication, authorization, and data classification requirements across pipelines and cross-domain transfers.
  • Write and maintain scripts (Python, Bash, or similar) to automate data processing, validation, and monitoring tasks.
  • Document data flows, system configurations, and standard operating procedures.

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