Data Operations Engineer (Hybrid) - 31009

HII•San Antonio, TX

1d•Hybrid

About The Position

As a member of Enlighten’s Data Operations Team, the Data Operations Engineer leads a technically focused team responsible for the reliability, uptime, and speed-to-delivery of mission-critical data sets. The role has a strong customer-facing focus and serves as the primary technical point of contact for stakeholders, translating mission requirements into technical workflows and ensuring data pipelines are automated, documented, and aligned with customer needs. The position oversees systems engineering and platform stability for high-velocity data across complex ecosystems. It manages the transition from reactive data fixes to an adaptive, self-healing platform, including oversight of Flow Owners who monitor, troubleshoot, and optimize data infrastructure while maintaining frequent communication with the client. The position is hybrid, with an average of 1–2 days per week at Enlighten’s San Antonio, Texas office.

Requirements

Must currently hold and maintain an active Top Secret U.S. Government Security Clearance; U.S. citizenship is required.
At least 9 years of relevant technical operations, systems engineering, or data management experience with a bachelor’s degree; or 7 years of relevant experience with a master’s degree in a related field; or a high school diploma or equivalent and 13 years of relevant experience.
Experience managing high-volume data flows and storage solutions, including distributed messaging queues, data orchestration engines, and cloud-native storage.
Familiarity with enterprise observability platforms and log analysis tools for monitoring system health and minimizing data discovery latency.
Deep understanding of network data, metadata fill rates, and log formats such as JSON and XML.
Fluency in managing extraction, translation, and loading (ETL) processes for rapid analytics.
Experience using SQL for data validation in collaboration with team members and the customer.
Ability to use scripting languages such as Python or Java to implement shared libraries that automate repetitive tasks and improve operational efficiency.
Exceptional ability to communicate technical concepts to non-technical stakeholders and translate customer mission requirements into technical specifications.
Must be able to obtain Security+ certification within 60 days of hire.
Must be able to work in a hybrid environment, averaging 1–2 days per week at the San Antonio, Texas office.
Flexibility to adapt to schedule changes as needed.

Nice To Haves

Prior experience in technical account management or a customer-facing engineering role.
Experience with distributed data processing and cloud-native storage solutions.
Prior experience supporting cyber or network security operations.
Knowledge of implementing automated Attribute Based Access Control (ABAC) or data masking within production pipelines.

Responsibilities

Serve as the lead liaison between the customer and the technical team; manage expectations, communicate technical roadmaps, and translate mission-specific data needs into engineering tasks.
Help manage daily DataOps team operations, accelerating data availability and minimizing latency between data identification and database availability.
Oversee deployment and maintenance of data flows using standardized templates and core libraries provided by the Engineering team.
Tune cluster performance and monitor pipelines to maintain data health and minimize discovery latency.
Drive the technical evolution of the data platform toward a proactive, automated, and adaptive operational model.
Coordinate technical exchanges so scripts, flow strategies, and successful practices are adapted across the ecosystem.
Implement automated quality gates and schema validations to protect data integrity before production.
Lead the decomposition and troubleshooting of complex systemic dataflow problems across distributed messaging, orchestration, and cloud environments.
Perform other duties as assigned.