Infrastructure Data Analytics Engineer
Overview
Lead data acquisition and integration initiatives across infrastructure platforms. Own end‑to‑end pipelines to deliver actionable insights for technology strategy and operational excellence. Drive automation and analytical capabilities at scale.
What You'll Do19
- 1Design and develop data ingestion processes from monitoring platforms CMDB and asset management systems Cloud platforms (Azure, AWS) Enterprise databases REST and GraphQL APIs SaaS and third‑party technology platforms
- 2Build and maintain scalable ETL/ELT pipelines to acquire cleanse transform validate and enrich data. Automate recurring collection and processing activities
- 3Develop complex SQL queries stored procedures views and data models. Create Python solutions for extraction transformation and quality validation
- 4Design and maintain Alteryx workflows for data preparation blending and analytics automation. Implement reusable transformation frameworks and standardized processing patterns
- 5Perform data reconciliation and quality assurance activities
- 6Analyze infrastructure and operational data to identify trends risks performance issues capacity constraints optimization opportunities
- 7Support executive reporting operational scorecards and KPI dashboards. Translate technical findings into business‑friendly recommendations
- 8Partner with infrastructure engineering operations and leadership teams to support data‑driven decision making
- 9Develop API integrations between internal and external platforms. Build automated workflows that reduce manual effort and improve timeliness
- 10Create reusable libraries and utilities that accelerate analytics delivery
- 11Follow SDLC methodologies including Agile delivery practices. Maintain source code in approved repositories using branching pull request peer review and merging standards
- 12Develop and maintain CI/CD deployment pipelines. Create technical documentation runbooks and deployment procedures
- 13Participate in release planning change management testing and production deployments. Ensure version control auditability and governance
- 14Support incident management and post‑release validation activities
- 15Ensure adherence to enterprise data governance security and compliance requirements. Maintain data lineage and metadata documentation
- 16Implement controls for data quality access management and operational resiliency. Support regulatory and audit requests
- 17Analyze infrastructure cloud and operational technology data. Apply knowledge of observability platforms (Datadog Splunk Dynatrace ServiceNow)
- 18Contribute to enterprise‑scale transformation or modernization programs
- 19Utilize programming languages SQL Python Alteryx Power BI Excel REST APIs JSON XML ETL ELT Data Modeling Data Quality Management DevOps SDLC GitHub GitLab Azure DevOps Version Control CI/CD Pipelines Release Management Test Automation Agile Scrum Infrastructure Monitoring Platforms
Requirements11
- 1Bachelor’s degree in a related field or equivalent work experience
- 2Five to seven years of statistical and/or data analytics experience
- 3Experience analyzing infrastructure cloud or operational technology data
- 4Familiarity with Power BI Tableau or similar visualization platforms
- 5Experience with Azure AWS Databricks Snowflake or enterprise data platforms
- 6Knowledge of Infrastructure Observability and Monitoring platforms Datadog Splunk Dynatrace ServiceNow
- 7Experience with CI/CD tools and release automation
- 8Understanding of data governance metadata management and data quality frameworks
- 9Ability to support enterprise‑scale transformation or modernization programs
- 10Strong SQL advanced Python Alteryx Power BI expertise
- 11Proficiency in REST APIs JSON XML ETL ELT Data Modeling Data Quality Management DevOps GitHub GitLab Azure DevOps
Salary Insight
$105 - $124k per year
Location
Required Skills
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