Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
Scoutfield Logo

See all jobs on Scoutfield

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
S&P Global

Sales Compensation Analyst, Pipeline Operations, Data Integrity

S&P Global

. Manage day-to-day execution and monitoring of critical data ingestion pipelines .

Posted 10/25/2026full-timeIndiaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in managing data ingestion pipelines, executing validation checks, and troubleshooting data discrepancies. Proficient in SQL, Python, and Power BI for operational reporting and data analysis.

Highest-signal resume keywords
Data Pipeline ValidationSQL Query OptimizationPython Automation ScriptingPower BI Dashboard CreationSOX Data Controls

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
SQLPythonAlteryxVBAData ValidationData ReconciliationData AnalysisData TroubleshootingOperational ReportingData Discrepancy Investigation
Soft Skills
Attention to DetailCommunication SkillsCollaboration
Tools & Technologies
Power BIExcelCRM SystemsBilling Systems
Industry Keywords
Data OperationsFinancial Systems SupportSales Compensation AnalysisOperational RunbooksStandard Operating Procedures

Tech Stack

Tools & technologies
PandasPythonSQLVBA

About the role

Key responsibilities & impact
  • Manage day-to-day execution and monitoring of critical data ingestion pipelines
  • Check table populations across billing systems, CRM feeds, and target tables
  • Execute daily script-based pre-calculation validation checks
  • Triage pipeline failures and data ingestion errors with global data architecture and systems teams
  • Execute automated end-of-month data loads and baseline calculations
  • Run, maintain, and enhance Python, Alteryx, and SQL reconciliation routines
  • Detect and eliminate transactional data discrepancies
  • Investigate data bugs and transaction discrepancies and create reproducible bug tickets
  • Partner with regional Revenue Operations and Technology teams to clean invalid source-system entries
  • Maintain operational runbooks and Standard Operating Procedures
  • Enforce SOX data controls and validation protocols
  • Standardize and validate monthly adjustment handling
  • Build and publish operational data health scorecards and pipeline status reports using Power BI and Excel
  • Research complex payment discrepancies with Commissions and Finance teams
  • Provide technical analysis and feedback to UK/US systems architects on recurring source data defects

Requirements

What you’ll need
  • 5+ years of technical experience in data operations, financial systems support, sales compensation analysis, or data pipeline validation
  • Proven ability to independently write, debug, and optimize complex SQL queries involving aggregations, subqueries, and multi-table joins
  • Hands-on experience building or maintaining automation scripts using Python (Pandas), Alteryx, or advanced VBA/macros
  • Exceptional diagnostic and troubleshooting skills with high attention to detail when working with complex financial datasets
  • Experience creating operational dashboards and reporting data in Power BI
  • Strong English communication skills, written and spoken
  • Experience and willingness to collaborate across global time zones (US, UK, and APAC)

Benefits

Comp & perks
  • Health care coverage designed for the mind and body
  • Generous time off
  • Access to learning and career development resources
  • Competitive pay
  • Retirement planning
  • Continuing education program
  • Company-matched student loan contribution
  • Financial wellness programs
  • Family benefits and perks
  • Retail discounts
  • Referral incentive awards