Sr. Software Engineer - Analytics Services Lead

Global C2 Integration Technologies•Reston, VA

10d•$100 - $100•Onsite

About The Position

GC2IT is seeking a Senior Software Engineer - Analytics Services Lead to own the design, delivery, performance, and operational evolution of analytics services for a large-scale, globally distributed mission platform. The role leads a portfolio of Java-based microservices and analytics/search infrastructure built around Elasticsearch, Logstash, Kibana, Grafana, and Vue.js 3 interfaces.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related technical field; four additional years of experience may substitute for a degree.
Ten or more years of software engineering, data platform engineering, search engineering, or analytics platform experience, including at least four years leading a major technical service area or team.
Strong experience building and operating analytics or search services in production.
Strong hands-on experience with Elasticsearch, Logstash, Kibana and/or Grafana, and Java-based backend services/microservices.
Demonstrated ownership of a technical analytics domain from architecture through operations.
Experience leading engineering teams or multi-team delivery for analytics/search platforms.
Strong troubleshooting skills across ingestion, indexing, query, UI, and platform layers.
Strong written and verbal communication skills, including the ability to explain performance, scale, and technical tradeoffs clearly.
Proven experience with indexed query optimization, field/composite/nested aggregations, rollups, summary generation, and caching strategies.
Experience tuning analytics and search services for strict latency and SLA-driven workflows.
Strong understanding of data ingestion, indexing, retention, search relevance, and performance tradeoffs.
Experience designing role-based analytics access patterns and user-facing analytics/reporting services.
Active Top Secret/SCI security clearance.

Nice To Haves

Master's degree in Data Engineering, Computer Science, Analytics, or a related field.
Experience with Vue.js 3 or similar frameworks for analytics dashboards and role-based user interfaces.
Experience building analytics and observability solutions in distributed microservices environments.
Experience with large-scale telemetry pipelines for logs, events, and metrics.
Familiarity with APM concepts, distributed tracing, and service-health correlation.
Experience with Grafana and ELK in the same observability/analytics ecosystem.
Experience with real-time or near-real-time event analysis in mission or operational systems.
Familiarity with RabbitMQ, event pipelines, or stream processing supporting analytics workloads.
Experience with multilingual analytics interfaces, region-specific reporting, capacity planning, cluster cost/performance tuning, RBAC, multi-tenant access, and reusable reporting/dashboard frameworks.
Experience supporting globally distributed platforms with variable network conditions and remote operational support models.

Responsibilities

Own the analytics services portfolio, including user-facing analytics, search and aggregate query services, event roll-up and nested aggregation services, telemetry/APM analytics, and analytics-facing administrative and visualization interfaces.
Lead design and delivery of Java-based microservices supporting analytics, search, aggregation, and reporting workflows.
Own analytics architecture for cached/indexed queries, composite aggregations across multiple fields, and nested aggregations supporting rollups and hierarchy-based summaries.
Ensure analytics services support both mission-facing reporting and operational telemetry analysis across services, infrastructure, and networking.
Tune and optimize analytic queries and service interactions to meet strict performance and latency requirements, including real-time transaction workflows.
Lead the design and operation of Elasticsearch, Logstash, Kibana, Grafana, and Vue.js 3 based analytics services and interfaces.
Define indexing, sharding, retention, query strategy, data models, and service contracts for distributed analytics workloads.
Own service-level health, scalability, and observability of analytics microservices.
Guide dashboards, visualizations, role-specific analytics views, and reporting capabilities.
Use telemetry and APM data to improve reliability, identify bottlenecks, support root-cause analysis, and lead major incident analysis where analytics or observability affects mission operations.