Data Operations Engineer (Hybrid) - 30862

HII•Columbia, SC

3d•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 datasets. The role has a strong customer-interface 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 focuses on systems engineering and platform stability for managing high-velocity data across complex ecosystems. It oversees the transition from reactive data fixes to an adaptive, self-healing platform, and manages Flow Owners who monitor, troubleshoot, and optimize data infrastructure while maintaining close communication with the client. The role is hybrid and requires working at the customer site in Fort Meade, Maryland, an average of two days per week, with flexibility to accommodate schedule changes.

Requirements

Must currently hold and maintain an active Secret U.S. Government Security Clearance, with the ability to obtain and maintain a TS/SCI 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.
Proven experience managing high-volume data flow and storage solutions, including distributed messaging queues, data orchestration engines, and cloud-native storage.
Strong 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 conjunction 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 hold current/active DoD 8140 / 8570 IAT Level II compliance certifications.
Must be able to work at the customer site in Fort Meade, Maryland, an average of two days per week, and be flexible to accommodate schedule changes.

Nice To Haves

Current TS/SCI-level clearance.
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 liaison between the customer and technical team; manage expectations, communicate technical roadmaps, and translate mission-specific data needs into actionable engineering tasks.
Assist in managing 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.
Facilitate technical exchanges so scripts, flow strategies, and successful approaches are shared across the ecosystem.
Implement automated quality gates and schema validations to ensure data integrity before production.
Assist with decomposing complex technical problems and troubleshoot systemic dataflow issues across distributed messaging, orchestration, and cloud environments.
Perform other duties as assigned.