Engineering Analytics Lead
Indexed description
Primary Responsibilities
- Design and develop analytical frameworks that integrate data across source control, CI/CD pipelines, quality platforms, observability tools, incident management systems, production change systems, security platforms, and software development tools.
- Define, implement, and govern engineering metrics that measure developer experience, software quality, release readiness, operational resilience, engineering productivity, and technology risk.
- Develop predictive models and data-driven insights to identify potential release risks, quality concerns, reliability issues, security vulnerabilities, and delivery bottlenecks before they impact production.
- Perform advanced statistical analysis, trend analysis, and failure analysis to identify patterns impacting software delivery performance and operational health.
- Create engineering scorecards, executive dashboards, and self-service reporting capabilities that provide visibility into engineering effectiveness and delivery outcomes.
- Analyze relationships between code changes, deployment activity, incidents, vulnerabilities, observability signals, and production outcomes to identify leading indicators of risk.
- Partner with Software Engineering, Site Reliability Engineering, Cybersecurity, Infrastructure, Risk, Architecture, and Product teams to establish common measurement frameworks and data definitions.
- Establish standards and best practices for engineering data collection, metric governance, and analytics platform design.
- Provide recommendations that improve software quality, developer productivity, deployment success rates, operational resilience, and customer outcomes.
- Translate complex data and technical findings into actionable recommendations for engineering leaders, executives, and business stakeholders.
- Present findings and insights at leadership reviews, architecture forums, engineering community events, and internal knowledge-sharing sessions.
- Contribute to the evolution of Developer Experience strategy through measurement, experimentation, benchmarking, and continuous improvement initiatives.
- Understand and adhere to the Company’s risk and regulatory standards, policies, and controls in accordance with the Company’s Risk Appetite.
- Identify risk-related issues requiring escalation to management.
- Promote an environment that supports a culture of belonging and reflects the M&T Bank brand.
- Maintain M&T internal control standards, including timely implementation of audit findings and regulatory requirements.
- Complete other related duties as assigned.
Supervisory/Managerial Responsibilities
No supervisory responsibilities.
Education And Experience Required
- 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.
- Advanced experience with data analysis, statistical modeling, predictive analytics, and dashboard development.
- Experience integrating data from multiple enterprise platforms and engineering systems.
- Proficiency with SQL and at least one analytical programming language such as Python or R.
- Experience working with large-scale operational, engineering, or observability datasets.
- Experience measuring Developer Experience, Engineering Effectiveness, DORA metrics, Flow Metrics, SPACE Framework, or related engineering productivity models.
- Experience with observability platforms such as Datadog, Splunk, Dynatrace, New Relic, Grafana, or Elastic.
- Experience integrating data from GitLab, GitHub, Jenkins, SonarQube, Jira, ServiceNow, CI/CD platforms, security scanning tools, and cloud environments.
- Knowledge of software development, release management, Site Reliability Engineering, and production operations.
- Advanced statistical analysis and machine learning experience.
- Experience developing predictive risk models and operational analytics.
- Strong storytelling and executive communication skills.
- Experience influencing strategy and decision-making through data.
- Experience leading enterprise analytics initiatives without direct people management responsibilities.
Location
Buffalo, New York, United States of America
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