Lead Software Engineer - Metrics and Analytics

Job summary

The Lead Engineer – Enterprise Metrics Platform, Data Engineering & Analytics will architect, build, and operate the enterprise technology metrics platform responsible for aggregating, transforming, governing, and visualizing data from multiple technology systems into a unified leadership reporting experience.

Qualifications

• and reporting needs into automated dashboards, data products, APIs, pipelines, and executive intelligence solutions.
• Primary Focus
• Enterprise data engineering and reporting architecture.
• Unified dashboard development and reporting automation.
• Technology systems integration and data aggregation.
• Executive analytics, visualization, and decision-support solutions.
• Technology metrics platform engineering and operational support.
• Scalable reporting, analytics, and self-service capabilities.
• Associate’s degree and a minimum of 7 years’ systems analysis and/or application development work experience or Bachelor's degree and a minimum of 5 years' systems analysis and/or application development work experience.
• In lieu of a degree, a combined minimum of 9 year’s education and/or relevant work experience, including a minimum of 5 years’ system analysis and/or application development work experience.
• Experience as a Lead Engineer, Data Engineer, Analytics Engineer, Software Engineer, Solution Architect, or similar role.
• Strong experience designing enterprise reporting platforms and analytics architectures.

Responsibilities

• Design and implement the enterprise technology metrics platform supporting Technology leadership reporting needs.
• Build automated integrations across Jira, ServiceNow, Zephyr, GitLab, Power BI, SharePoint, Workday, Snowflake, and related systems.
• Develop scalable data pipelines, APIs, ingestion frameworks, and transformation processes that standardize reporting data across disparate platforms.
• Implement metric calculation engines that execute approved business rules and reporting logic defined by governance teams.
• Build executive dashboards, scorecards, drill-down experiences, trend visualizations, and self-service analytics capabilities.
• Establish enterprise reporting architecture, metadata standards, master data management, and governance controls.
• Design reusable reporting components that support Tech ART Playbooks, Agile Operations reporting, SDLC dashboards, operational scorecards, and executive reviews.
• Build automated monthly reporting processes that reduce manual data collection and consolidation activities.
• Enable near real-time reporting and monitoring capabilities across Technology organizations where source-system data and access patterns support it.
• Develop data quality controls, reconciliation routines, monitoring, exception handling, and auditability capabilities.
• Partner with platform owners to optimize data accessibility, reporting performance, and integration reliability.
• Support advanced analytics initiatives including trend analysis, predictive insights, anomaly detection, and performance benchmarking.

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