Data Ops Engineer

Data Scientist

Xenith Solutions is a small family focused business where we focus on taking care of our employees and customers equally. We are focused on serving Federal / Civilian, Defense and Intelligence organizations with superior service. If you want to be a part of a rapidly growing business with an exceptional culture, then you want to be a part of the Xenith Solutions family. Xenith Solutions is seeking a highly skilled and motivated Data Scientist to join our team in developing innovative solutions to challenging national problems in support of the Navy, DoD, and Intel communities engineering and technology needs. You should possess deep expertise in Python, data science libraries, and visualization/BI tools to lead advanced analytics initiatives supporting mission-critical objectives. The ideal candidate brings both strong technical acumen and domain experience working with Department of Defense (DoD) and/or Intelligence Community (IC) data sources such as SIGINT, GEOINT, or other multi-INT data.

Responsibilities:

• Design, build, and maintain real-time data ingestion pipelines.
• Ensure the reliable flow of streaming data from a wide range of sources into our data platform, ensuring data quality, observability, and scalability.
• Partner closely with data engineers, platform engineers, and analytics teams to deliver trustworthy, low-latency data that supports operational decisions.
• 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 and prevent 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/SCI
• Bachelor 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. Tools
• Apps/Platforms: NiFi, Kafka, Grafana, Prometheus, Apache Flink/Spark Streaming, Snowflake, Elasticsearch, Kafka, MQTT, JMS Operating Systems: Windows, Linux (RedHat).