Business Systems Analyst — Enterprise Support Data & Analytics

Business Systems Analyst — Enterprise Support Data & Analytics
Location: Remote (US ONLY)
Duration: 12 months, with potential extension 
Pay rate: $70 - $75/hr on W2
Benefits: Health, Dental, Vision, 401K, PTO
Note: This is a W-2-only position. We do not offer visa sponsorship and cannot accept H-1B, F-1/STEM OPT, 1099, C2C, or C2H arrangements.

Job Summary

We are seeking aBusiness Systems Analyst IV to own and evolve the data systems supporting our client's Enterprise Support. This role is responsible for the health and continued improvement of the data layer, includingSQL, Hive tables, data pipelines, data models, and dashboards.

The ideal candidate is more than a reporting analyst, must have a hands-on data professional who can take loosely defined business problems, determine the appropriate technical approach, and independently deliver scalable solutions.

You will work across the full data lifecycle, from pipeline development and data modeling to operational reporting, governance, automation, and data quality. You will also have opportunities to applyAI and LLM tooling to accelerate analytical workflows and extract insights from unstructured support data.

The work is highly visible: reporting and analytics produced by this role help Enterprise Support leadership make decisions aroundstaffing, coverage, prioritization, and operational performance.

Job Responsibilities

• Own the day-to-day health and reliability of theEnterprise Support data layer, including pipelines, Hive tables, SQL queries, and dashboards.
• Design and builddata models and warehouse structures for new reporting and analytical requirements.
• Make technical and modeling decisions independently rather than relying solely on predefined specifications.
• Build, maintain, and improveproduction ETL/ELT pipelines, including scheduling, dependency management, monitoring, failure resolution, and backfills.
• Maintain a documentedsource of truth for Enterprise Support metrics, including metric definitions, data ownership, and freshness.
• ApplyAI and LLM tooling appropriately to accelerate data analysis and identify signals within unstructured support information such as ticket notes and resolution summaries.
• Identify opportunities to automate manual processes and improve pipeline reliability and operational efficiency.
• Monitor data quality and pipeline performance, investigate discrepancies, and resolve data issues.
• Deliver recurringweekly, monthly, and quarterly reporting, as well as ad hoc analyses for business stakeholders.
• Develop and maintain dashboards and operational reporting used by Enterprise Support leadership.
• Establish and maintain standards fordata naming, documentation, schema changes, and dataset lifecycle management.
• Proactively identify gaps in data quality, governance, reporting coverage, and metric definitions.
• Communicate project status, recommendations, risks, and blockers clearly and proactively in writing.
• Partner with the manager and relevant stakeholders to translate business needs into scalable data solutions.

Must Have Qualifications

• 6–7 years of experience in data analytics, business analytics, analytics engineering, or a related field.
• AdvancedSQL skills with hands-on experience working with large-scale datasets.
• Experience using distributed query engines such asPresto and Hive.
• Demonstrated experience building and maintainingproduction data pipelines, including scheduling, dependency management, backfills, monitoring, and failure resolution.
• Strong understanding ofdata modeling and warehouse design, including schema design, data grain, partitioning, and documentation.
• Experience making data architecture or modeling decisions rather than solely maintaining existing solutions.
• Practical experience applyingAI or LLM tooling within data or analytical workflows.
• Experience developingdashboards and operational reporting.
• Ability to work independently in an environment where requirements may be loosely defined.
• Strong written communication skills, including the ability to clearly document technical work, recommendations, status, and blockers.
• Bachelor's degree inComputer Science, Information Systems, Analytics, a quantitative discipline, or equivalent practical experience.

Preferred Qualifications

• Experience withdata governance, including metric catalogs, lineage, table ownership, schema change management, and dataset lifecycle management.
• Experience supporting anIT, enterprise support, or technical operations organization.
• Experience withPython or similar scripting languages for data transformation and automation.
• Experience maintainingoperational metrics, SLA reporting, and service-performance dashboards.
• Experience working with large-scale enterprise datasets and distributed data platforms.
• Experience identifying and resolving data quality and reporting coverage gaps.
• Experience using AI/LLM technologies to analyzeunstructured operational or support data.