Summary:
As a Business Intelligence Engineer leading the Data vertical, you will own the delivery of the metrics layer for Company's end-to-end payroll process. You will build and maintain data pipelines that enable near-real-time tracking and reporting of pay defects, surface metrics through intuitive dashboards for Payroll leadership, and partner with the Metrics and Quality verticals to translate their requirements into scalable data products. You will work directly with payroll operations stakeholders across APAC, EMEA, LATAM, and North America to understand their data needs and deliver solutions that drive confident decision-making.
This role sits at the intersection of data engineering, business intelligence, and payroll operations. You will work with large-scale datasets spanning multiple payroll vendors, time and attendance systems, and defect tracking platforms. You will define validation rules for automated defect detection, build pilot datasets across multiple pay frequencies and geographies, and develop the shadow-mode analytics infrastructure that proves the accuracy of our deterministic classification models against legacy systems.
Responsibilities:
- Own the data roadmap for the MAPT Data vertical, addressing key customer pain points and business requirements across Payroll operations.
- Design, build, and maintain data pipelines and ETL processes that power payroll metrics, defect tracking, and operational dashboards.
- Build and maintain self-service dashboards and reporting tools that surface payroll quality metrics (DPMO, defect rates, resolution timelines) for S-team and Payroll leadership audiences.
- Develop pilot datasets covering multiple pay frequencies and geographies to validate deterministic defect detection models.
- Partner with Metrics and Quality verticals to translate business requirements into data products, including automated defect classification and root cause attribution.
- Conduct deep-dive analyses on pay defect trends, root causes, and process effectiveness across 35 countries.
- Define and document data validation rules in partnership with BI analysts and payroll operations teams.
- Establish data quality controls to ensure metrics reliability and consistency across global payroll systems.
- Support vendor data integration strategy, including retro-correction report analysis and monetary impact quantification.
Requirements:
- 5 years of experience working with large-scale, complex datasets in a business intelligence or data engineering capacity.
- Background in statistics, computer science, mathematics, or a related quantitative field.
Required Skills:
- Strong proficiency in SQL and experience building data pipelines and ETL processes.
- Experience with data visualization tools (QuickSight, Tableau, or similar) and building self-service dashboards.
- Demonstrated ability to translate business requirements into analytical plans and execute independently.
- Experience with Python or similar scripting languages for data analysis and automation.
- Strong analytical mindset with the ability to decompose ambiguous problems into structured approaches.
- Excellent written and verbal communication skills, with experience presenting data insights to senior leadership.
- Experience working with global datasets across multiple regions and regulatory environments is a plus.
- Familiarity with payroll systems, HR data, or financial operations data is a plus.
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