Job description

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 a Business 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, including SQL, 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 apply AI 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 around staffing, coverage, prioritization, and operational performance . Job Responsibilities • Own the day-to-day health and reliability of the Enterprise Support data layer , including pipelines, Hive tables, SQL queries, and dashboards. • Design and build data 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 improve production ETL/ELT pipelines , including scheduling, dependency management, monitoring, failure resolution, and backfills. • Maintain a documented source of truth for Enterprise Support metrics , including metric definitions, data ownership, and freshness. • Apply AI 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 recurring weekly, 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 for data 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. • Advanced SQL skills with hands-on experience working with large-scale datasets. • Experience using distributed query engines such as Presto and Hive . • Demonstrated experience building and maintaining production data pipelines , including scheduling, dependency management, backfills, monitoring, and failure resolution. • Strong understanding of data 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 applying AI or LLM tooling within data or analytical workflows. • Experience developing dashboards 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 in Computer Science, Information Systems, Analytics, a quantitative discipline , or equivalent practical experience. Preferred Qualifications • Experience with data governance , including metric catalogs, lineage, table ownership, schema change management, and dataset lifecycle management. • Experience supporting an IT, enterprise support, or technical operations organization . • Experience with Python or similar scripting languages for data transformation and automation. • Experience maintaining operational 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 analyze unstructured operational or support data . Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation. #TMMT

Requirements

Must-haves

Business Systems Analyst — Enterprise Support Data & Analytics
Location: Remote (US ONLY)
Duration: 12 months, with potential extension
Pay rate: $70 - $75/hr on W2
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.
The work is highly visible: reporting and analytics produced by this role help Enterprise Support leadership make decisions around staffing, coverage, prioritization, and operational performance .
Own the day-to-day health and reliability of the Enterprise Support data layer , including pipelines, Hive tables, SQL queries, and dashboards.
Design and build data 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 improve production ETL/ELT pipelines , including scheduling, dependency management, monitoring, failure resolution, and backfills.
Maintain a documented source of truth for Enterprise Support metrics , including metric definitions, data ownership, and freshness.
Apply AI 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 recurring weekly, 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 for data naming, documentation, schema changes, and dataset lifecycle management .

Nice-to-haves

Experience with data governance , including metric catalogs, lineage, table ownership, schema change management, and dataset lifecycle management.
Experience supporting an IT, enterprise support, or technical operations organization .
Experience with Python or similar scripting languages for data transformation and automation.
Experience maintaining operational 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 analyze unstructured operational or support data .

Application prep

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Keywords to mirror

sqlaillmpython

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Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto