Data Analytics/Metrics Engineer
DataStaff, Inc. is seeking a Data Analytics/Metrics Engineer for a long-term contract opportunity with one of our direct clients in Albany, NY
Job Description:
The Data Analytics/Metrics Engineer will use data analytics, observability, scripting, automation, and enterprise application administration to improve operational efficiency, application reliability, and data-driven decision-making. You will strengthen monitoring and analytics capabilities across complex, multi-tier application environments, transform operational data into actionable insights, automate repetitive processes, and improve 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 do
- 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.
- 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.
- 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.
- 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.
- 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.
- Improve operational visibility, use of Splunk analytics, manual-effort reduction through scripting automation, application issue identification, reporting accuracy, and reliability across enterprise application and integration environments.
What you'll bring
- 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.
Nice to have
- 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.
DataStaff offers W-2 employment opportunities with a competitive benefits package. Many of our positions include medical, dental, and vision insurance, plus paid vacation, sick leave, and holidays. Recognizing that many of our assignments are long-term, DataStaff also offers a 401(k) retirement savings plan, with employees becoming eligible after six months of employment.