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Data Operations Engineer (TS​/SCI) with Security Clearance

Job in San Diego, San Diego County, California, 92101, USA
Listing for: Zachary Piper Solutions, LLC
Full Time position
Listed on 2026-08-10
Job specializations:
  • IT/Tech
    Data Engineering, Data Analyst, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 150000 - 230000 USD Yearly USD 150000.00 230000.00 YEAR
Job Description & How to Apply Below
Zachary Piper Solutions is seeking a TS/SCI cleared Data Operations Engineer to support the United States Air Force's Joint Fires Network program in San Diego, California. This full-time, on-site role focuses on managing real-time data ingest operations, monitoring data quality, and supporting the delivery of mission-critical data feeds. The ideal candidate will have strong experience in data engineering, scripting, data visualization, and operational support within technical environments.

Period of Performance (Contract Length):
* 5 years.

* Program has been awarded and is live.

* Currently in month 7 out of 5 years.
Location and Work Environment:
* Full-time on-site role in San Diego, California, supporting operational data pipelines and mission systems. Travel up to 15% to Oahu, Hawaii may be required, including long-distance trips to additional government or contractor facilities.
* Position operates in a low supervision independent capacity, working with cross-domain groups across the nation. Responsibilities:
* Support continuous data ingest operations, monitoring data feeds, pipeline health, and overall data quality.
* Visualize and interpret data findings through dynamic reports and dashboards for leadership and users.
* Use data manipulation and visualization tools to communicate real-time and historical trends.
* Collaborate with platform, software, and data engineering teams to reconfigure pipelines for improved reliability.
* Work with data in multiple formats including Excel, CSV, JSON, and XML.
* Support incident management processes including issue documentation, resolution, and root-cause analysis for recurring data outages.
* Develop and maintain software to automate monitoring of real-time data feeds, including alerts for timeliness, lineage, volume, and distribution issues.
* Leverage historical pipeline data to identify improvements in ingest performance and reliability.
* Assist with designing, developing, testing, and implementing web-based collaboration and reporting tools.
* Demonstrate proficiency in Python or Bash scripting for analytics, automation, and data operations.
* Utilize open-source analytics and visualization tools to monitor system performance.

Qualifications:

* Must have an active TS/SCI clearance
* Bachelor's degree in Computer Science, Mathematics, Engineering, Physics, Information Systems, or related field.
* 5-15 years of experience in data engineering or related experience
* At least 1+ years of experience with real-time data streaming
* Strong experience handling structured and unstructured data across various formats.
* Proficiency with Python

* Experience with JSON or XML

* Experience with any of the following data streaming tools such as:
Apache (Kafka, Pulsar, Flink, Storm, Samza, Spark, Beam, Redpanda, or NiFi), Confluent Platform, Stream Native Platform, Cloudera Streaming, AWS Kinesis Data Streams/Firehose, AWS MSK, Google Cloud Data Stream, Google Dataflow (stream mode), RabbitMQ, NATS Jetstream, ZeroMQ.
* Experience with Linux OS

Preferred Experience:

* Experience with intelligence and C2 data sets (ELINT, COMINT, MASINT, GEOINT).
* Knowledge of data mining, data modeling, statistics, and machine learning.
* Familiarity with Kubernetes cluster deployment and management. Compensation:
* Pay range: $150,000 - $230,000 (Based on years of relevant experience) Benefits:
* Comprehensive benefits package including medical, dental, vision, 401k, 20 days of paid time off, 11 federal holidays, and sick leave. Application Period:
Opens on 08/10/2026 and will be accepted for at least 30 days from the posting date. #LI-NJ1 #LI-Onsite
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