Lead Software Engineer - Metrics and Analytics

M&T Bank•Buffalo, NY

2d•$116,400 - $194,000•Onsite

About The Position

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. This role serves as the technical owner for the enterprise technology reporting ecosystem, integrating Jira, ServiceNow, Zephyr, GitLab, Power BI, SharePoint, Workday, Snowflake, and related platforms into a scalable analytics architecture that enables standardized reporting across Technology. Working closely with the Business Systems Analyst, the Lead Engineer translates metric definitions, business rules, governance requirements, and reporting needs into automated dashboards, data products, APIs, pipelines, and executive intelligence solutions.

Requirements

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.
Experience building integrations using APIs, ETL/ELT pipelines, event-driven architectures, and enterprise data platforms.
Experience with Power BI, SQL, dashboard engineering, reporting automation, and data visualization technologies.
Strong software engineering and solution architecture experience.
Experience working with large-scale enterprise data environments.
Ability to translate business requirements into scalable technical solutions.
Strong stakeholder engagement and technical leadership skills.

Nice To Haves

Experience integrating Jira, ServiceNow, GitLab, Zephyr, Workday, SharePoint, Snowflake, Azure, or similar enterprise platforms.
Experience supporting enterprise Agile, SDLC, DevOps, or technology governance initiatives.
Knowledge of DORA metrics, Agile metrics, SDLC data models, DevOps reporting, and engineering effectiveness frameworks.
Experience with Data Warehousing, Lakehouse architectures, Data Mesh principles, and modern analytics platforms.
Experience within financial services, regulatory environments, or enterprise-scale technology organizations.
Certifications in Azure, Data Engineering, Power BI, Cloud Architecture, SAFe, DevOps, or software engineering disciplines.

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.
Develop scalable visualization standards and user experiences optimized for executive consumption.
Establish engineering standards for dashboard development, reporting automation, release management, and supportability.
Mentor engineering resources supporting analytics, integrations, reporting tools, and data platforms.