Data Operations Engineer

Saicinc — United States · Posted ~3 hours ago

Mid Full-time Onsite

Skills

Data pipelines Real-time data ingestion Data quality Observability Streaming data Streaming

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Summary ✨ AI‑Generated

An on-site engineering role focused on designing and maintaining real-time data ingestion systems. The position involves improving data reliability, monitoring pipelines, and collaborating with engineering teams.

Highlights

Full-time engineering role focused on real-time data systems, reliability, and building trustworthy data flows for operational needs.

Description

Job ID 2615848 Location San Diego, CA, US Date Posted 2026-08-21 Category Engineering and Sciences Subcategory Systems Engineer Schedule Full-Time Shift Day Job Travel Yes - 10% of the time Minimum Clearance Required TS.SCI Clearance Level Must Be Able to Obtain None Potential for Remote Work ORA_ON_SITE Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a wide range of sources into our data platform, ensuring data quality, observability, and scalability. You'll partner closely with data engineers, platform engineers, and analytics teams to deliver trustworthy, low-latency data that supports operational decisions. This position is on-site in San Diego, CA. Aid the team in delivering continual data feeds to users and monitoring the status of the health of data quality and overall data ingest. Aid the team in delivering continual data feeds to users and monitoring the status of the health of data quality and overall data ingest.Build resilient pipelines with appropriate backpressure, prioritization, retries, and error-handling strategies.Employ a variety of data manipulation and visualization tools to effectively convey status and historical trends to leadership, users, and data team.Collaborate with platform, software, and other data engineers to (re)configure data ingestion pipelines to be more reliable.Work with data in a variety of formats including Excel, CSV, JSON, and XML.Support the incident management process to ensure that incidents are documented and resolved quickly. Perform root cause analysis to understand andprevent repeated occurrences of data outages.Develop and maintain software to automate monitoring of real-time feeds and alert for timeliness, volume, lineage, and distribution data issues. Process learnings and rely on historical data from data pipelines, translating them into actionable steps to improve data ingest.Partner with security and governance teams to enforce encryption, authentication authorization, and data classification. Demonstrate proficiency with frequent-used scripting language (Python, bash) commonly used in data science applications and data analytics. Qualifications U.S. citizenship and an active TS/SCIBachelor of Science required in the following preferred fields Computer Science, Mathematics, EE, Physics, Information Systems, or Information Technology.3+ years of experience in data engineering, data operations, or DevOps roles supporting production data pipelines. ToolsApps/Platforms NiFi, Kafka, Grafana, Prometheus, Apache Flink/Spark Streaming, Snowflake, Elasticsearch, Kafka, MQTT, JMS Operating Systems Windows, Linux (RedHat). Target salary range $200,001 - $240,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.