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Jobs/Senior Data Scientist Role/EarnIn - Senior Business Systems Analyst
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EarnIn

EarnIn - Senior Business Systems Analyst

Mexico City, Mexico; Remote, Mexico - Hybrid2d ago
In OfficeSeniorLATAMSenior Data ScientistReportingDocumentationADPRESTSOAPSQLData AnalysisPythondbtData GovernanceData QualityBusiness IntelligenceWorkdayGreenhouse

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Requirements

• Support cross-functional testing and validation efforts through automated reporting, data checks, and failure detection • Partner with functional teams (e.g., Talent, Payroll, Benefits) to enable effective test plans and issue identification • Contribute to a high-quality user experience by ensuring data accuracy and system reliability across workflows • Collaboration & Communication • Partner with Core HCM architects and business process administrators across SKUs including Talent and Advanced Compensation, to ensure cohesive, end-to-end system design • Translate complex technical concepts into clear insights for non-technical audiences • Collaborate across HR, IT, Finance, and vendors to align solutions with business needs • Security & Compliance • Ensure integrations meet security, privacy, and compliance standards • Manage secure data transfers and authentication methods across systems • 4+ years of experience with Workday integrations and tools such as: Workday Studio, EIB, Core Connectors, Workday Web Services / APIs • Experience integrating Workday with systems such as: • ADP / global payroll vendors • Okta/identity management • Greenhouse / ATS • Benefits providers (e.g., Navia, Bswift) • Finance systems (e.g., Pigment, NetSuite, Zip, Navan) • Data formats: XML, JSON, CSV • Integration technologies: REST / SOAP APIs, SFTP • SQL and data analysis skills • Familiarity with AI/ML concepts or tools applied to data workflows (e.g., anomaly detection, automation, or data enrichment) • Experience with data validation and troubleshooting • Strong ability to translate complex technical concepts into clear, actionable insights for non-technical stakeholders • Strong problem-solving ability, experience with uncovering root causes, and executing action plans rapidly and thoughtfully. • Experience with HR data governance • Experience working with or supporting AI-enabled data platforms, pipelines, or analytics tools • Exposure to tools like Python, dbt, or modern data platforms is a plus • 2+ years of experience working with a Workday implementation partner (e.g., Topbloc, Deloitte, Accenture) • SUCCESS METRICS • SUCCESS METRICS • Reliable, high-performing integrations with minimal failures • Accurate, timely, and secure data delivery across systems • Reduced manual effort through automation and intelligent workflows • Measurable cost savings driven by optimized architecture and efficient data processing • Scalable, well-documented systems that support business growth • Improved data quality and user experience through proactive monitoring and validation • #LI-Remote #LI-Hybrid

Responsibilities

• Workday Integrations & Data Management • Design, build, test, and maintain Workday integrations using tools such as EIB, Core Connectors, Workday Studio, and APIs • Manage integrations across payroll, benefits, identity management, finance systems, data warehouses, and other HR platforms • Ensure data integrity through transformation logic, mapping, and bulk data operations • Monitoring, Reporting & Data Delivery • Monitor integrations, troubleshoot failures, and resolve data discrepancies • Develop and maintain reporting, data feeds, and pipelines to support HR, Finance, and business intelligence platforms • Proactively identify issues using logs, reporting, and automated alerts • Architecture, Automation & AI • Act as a bar raiser for integration and data architecture, promoting best practices in scalability, performance, cost efficiency, and user experience • Drive architectural decisions that balance cost, performance, and end-user experience • Identify and implement automation and AI-enabled solutions to improve data quality, anomaly detection, and operational efficiency • Partner with engineering and data teams to support AI-ready data pipelines

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