JOB DESCRIPTION

Transform technology into opportunity as a Data Analytics & Metrics Engineer. In this role, you will leverage data analytics, observability, scripting automation, and enterprise application administration to improve operational efficiency, application reliability, and data-driven decision-making.

You will lead initiatives to strengthen monitoring and analytics capabilities across complex, multi-tier application environments. You will transform operational data into actionable insights, automate repetitive processes, and improve the performance.

The ideal candidate combines strong analytical and troubleshooting skills with hands-on technical expertise, automation capabilities, and the ability to collaborate across application development, infrastructure, integration, and business teams.

WHAT YOU’LL OWN & DELIVER

Architect the Data Analytics & Automation Strategy

·         Define and implement a roadmap for expanding operational analytics, intelligent monitoring, and automation across enterprise applications and infrastructure.

·         Identify opportunities to replace manual analysis and repetitive operational tasks with reusable scripts, automated workflows, and data-driven processes.

·         Establish standards for log analytics, data extraction, error analysis, reporting, and operational dashboards.

Drive Splunk Analytics & Observability

·         Design, develop, and optimize Splunk searches, dashboards, reports, and alerts to monitor application health, system performance, and operational trends.

·         Analyze large volumes of application logs, HTTP status codes, API transactions, and infrastructure events to identify patterns, anomalies, and recurring issues.

·         Develop advanced SPL queries to aggregate events, normalize dynamic URL paths, identify high-volume failures, and compare daily, weekly, monthly, and quarterly trends.

·         Establish operational KPIs and metrics to measure error rates, application reliability, incident trends, and service performance.

·         Translate complex log data into clear insights and actionable recommendations for technical teams and management.

Lead Scripting & Process Automation

·         Design and implement automation solutions using Python, Shell/Bash scripting, and Java to streamline data extraction, log processing, system checks, reporting, and operational workflows.

·         Develop reusable scripts and utilities to reduce manual effort, improve consistency, and accelerate troubleshooting.

·         Automate recurring reports, file analysis, exception identification, and operational data processing.

·         Integrate automation with existing monitoring, application support, and deployment processes.

·         Establish coding, documentation, scheduling, error-handling, and maintenance standards for reliable automation.

Establish Data-Driven Operational Excellence

·         Define meaningful operational metrics and reporting standards to support proactive issue detection and continuous improvement.

·         Identify trends in incidents, system errors, integration failures, and file-transfer activity.

·         Present analytics findings, risk indicators, and improvement opportunities to technical leadership and business stakeholders.

·         Promote knowledge sharing, technical documentation, automation reuse, and continuous improvement across teams.

·         Evaluate the effectiveness of automation and analytics initiatives using measurable outcomes such as time saved, reduced manual effort, faster incident investigation, and improved monitoring coverage.

WHAT YOU’LL NEED TO SUCCEED

Required Qualifications

·         Bachelor’s degree in related discipline

·         5 years of progressive experience in IT operations, data analytics, application support, systems administration, software engineering, or a related technical discipline.

·         Strong hands-on experience with Splunk Enterprise/Dynatrace, SPL, log analysis, dashboards, reporting, and operational monitoring.

·         Demonstrated scripting or programming experience using Python, Shell/Bash, Java, or comparable automation technologies.

·         Experience troubleshooting enterprise applications, analyzing logs, identifying recurring issues, and performing root cause analysis.

·         Familiarity with MuleSoft integrations, REST APIs, JSON payloads, API monitoring, and HTTP status-code analysis.

·         Experience with Twilio communication APIs, messaging integrations, notification workflows, or delivery monitoring.

·         Strong analytical and problem-solving skills, with the ability to translate technical findings into actionable recommendations.

·         Experience developing technical documentation, operational reports, reusable scripts, and repeatable support procedures.

·         Excellent communication and collaboration skills, with the ability to work across development, infrastructure, operations, and business teams.

Preferred Qualifications

·         Experience administering or supporting JBoss / JBoss EAP application environments.

·         Advanced Splunk SPL skills, including regular expressions, field extraction, event correlation, statistical aggregation, time-based comparisons, and dashboard development.

·         Experience automating operational processes, reporting, file analysis, or system administration tasks using Python and Shell scripting.

·         Familiarity with Java-based enterprise applications, Linux/Unix administration, SFTP workflows, and production support.

·         Experience with SQL, relational databases, Git, Jira, CI/CD tools, or cloud monitoring platforms.

·         Knowledge of incident management, problem management, release coordination, and service reliability practices.

·         Experience mentoring technical team members, coordinating cross-functional initiatives, or leading technical improvement projects.

·         Familiarity with healthcare, government, or other enterprise environments requiring strong operational controls and documentation.

LEADERSHIP & PERFORMANCE EXPECTATIONS

·         Promote an automation-first mindset and encourage continuous improvement.

·         Establish measurable objectives for analytics quality, monitoring coverage, and operational efficiency.

·         Communicate technical risks and analytical findings clearly to management and stakeholders.

·         Prioritize initiatives based on business impact, operational risk, and potential efficiency gains.

·         Encourage collaboration, technical development, knowledge sharing, and standardized engineering practices.