Data Operations Lead (Hybrid) - 27895

HII's Mission Technologies division•Columbia, MD

7d•Hybrid

About The Position

As a member of the Data Operations Team at Enlighten, you will lead a technically focused team responsible for the reliability, uptime, and speed-to-delivery of mission-critical data sets. This role requires a heavy focus on customer interface, serving as the primary technical point of contact for stakeholders. You will translate complex mission requirements into technical workflows, ensuring that our data pipelines are automated, documented, and precisely aligned with customer needs. This position focuses on the systems engineering and platform stability required to manage high-velocity data across complex ecosystems. You will oversee the transition from reactive data fixing to an adaptive, self-healing platform, managing the "Flow Owners" who monitor, troubleshoot, and optimize data infrastructure while maintaining high-touch communication with the client.

Requirements

Security Clearance - Must have a current Secret level U.S. Government security clearance; U.S. Citizenship required.
Must have 9+ years in technical operations, systems engineering, or data management with a Bachelor’s degree; OR 7 years relevant experience with Masters in related field; OR High School Diploma or equivalent and 13 years relevant experience.
Distributed Systems & Cloud Platforms: Proven experience managing high-volume data flow and storage solutions, specifically distributed messaging queues, data orchestration engines, and cloud-native storage.
Observability & Log Analysis: Strong familiarity with enterprise observability platforms and log analysis tools for monitoring system health and minimizing data discovery latency.
Data Standards: Deep understanding of network data, metadata fill rates, and various log formats such as JSON and XML.
ETL Management: Fluency in managing extraction, translation, and loading (ETL) processes to enable rapid analytics.
Data Validation: Experience with Structure Query Language (SQL) for the purposes of data validation in conjunction with members of the team and the customer.
Scripting for Automation: Ability to utilize scripting languages (e.g., Python or Java) to implement shared libraries that automate repetitive tasks and improve operational efficiency.
Technical Communication: 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, spending an average of 1-2 days per week at our Columbia, MD office. Flexibility is essential to adapt to schedule changes as needed.

Nice To Haves

TS/SCI eligibility preferred.
Customer Success Background: Prior experience in a technical account management or customer-facing engineering role.
Scalable Architectures: Experience with distributed data processing and cloud-native storage solutions.
Security Operations: Prior experience supporting cyber or network security operations.
Governance & Access: Knowledge of implementing automated Attribute Based Access Control (ABAC) or data masking within production pipelines.

Responsibilities

Customer Interface & Engagement: Serve as the lead liaison between the customer and the technical team. You will manage expectations, communicate technical roadmaps, and translate mission-specific data needs into actionable engineering tasks.
Operational Leadership: Manage the daily operations of the DataOps team, focusing on accelerating data availability and minimizing the latency between initial data identification and final database availability.
Systems Engineering Oversight: Oversee the deployment and maintenance of data flows using standardized templates and core libraries provided by the Engineering team.
Performance Tuning: Responsible for immediate cluster performance tuning and pipeline monitoring to ensure data health and discovery latency are minimized.
Strategic Alignment: Drive the technical evolution of the data platform, moving the organization from a reactive maintenance state toward a proactive, automated, and adaptive operational model.
Ecosystem Coordination: Facilitate technical exchanges to ensure scripts, flow strategies, and wins in one area of the ecosystem are adapted and utilized across others.
Quality Governance: Implement automated "Quality Gates" and schema validations to ensure data integrity before it reaches production environments.
Technical Troubleshooting: Lead the decomposition of complex technical problems and troubleshoot systemic dataflow issues across distributed messaging, orchestration, and cloud environments.
Other duties as assigned.