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Open nowPosted today

Sales Compensation Analyst

S&P GLOBAL ASIAN HOLDINGS PTE. LTD.

Pay
SGD 13,000 – SGD 16,000 a Monthly
Where
Central, Singapore
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Your applicationOpen nowSales Compensation AnalystS&P GLOBAL ASIAN HOLDINGS PTE. LTD. · Central, Singapore

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Share of postings closed within
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  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: posted today

The posting

Sales Compensation Analyst (Systems Architecture & Data Pipelines)

Role Overview:

The Sales Compensation Analyst (Systems Architecture & Data Pipelines) serves as a key technical developer and systems specialist bridging Finance, Revenue Operations, and Technology. In this role, you will be responsible for designing, optimizing, and maintaining database schemas, ETL pipelines, and data warehouse staging layers that ingest massive volumes of commercial transaction and billing data. You will ensure that downstream calculation engines and BI platforms receive performant, validated, and normalized data feeds.

Key Responsibilities:

Database Schema Design & Pipeline Optimization

  • Design, build, and optimize relational database tables, views, indexed views, and stored procedures supporting large sales compensation datasets.
  • Partner with Business Intelligence and Data Engineering teams to evaluate data warehouse architecture (Snowflake/Azure/SQL Server), contributing to schema evolution and data dictionary updates.
  • Optimize heavy data extraction queries, indexing strategies, and execution plans to minimize batch processing runtimes during critical financial close windows.
  • Identify and eliminate pipeline bottlenecks, schema drift, and data ingestion lags between CRM systems (Salesforce), billing platforms, and compensation calculation engines.

Automated ETL & Integration Workflows

  • Build, deploy, and maintain robust data integration pipelines using SQL, Python (Pandas/NumPy), and workflow orchestration tools (e.g., Alteryx, Airflow, or SSIS).
  • Engineer automated data transformation steps that map unstructured and multi-source commercial data into standardized dimensional models (Fact/Dimension schemas).
  • Monitor scheduled data batch runs, resolving runtime errors, connection dropouts, and API ingest exceptions immediately.
  • Build automated failover, alerting, and logging mechanisms that trigger automated notifications whenever staging tables show row count disparities or anomalous data types.

Systemic Data Diagnostics & Root Cause Analysis

  • Lead technical root cause investigations on systemic calculation anomalies originating from data ingestion bugs, logic mismatches, or source-system schema modifications.
  • Trace transaction histories through staging layers and transformation scripts back to initial CRM transaction entries to verify data lineage and accuracy.
  • Deploy automated regression testing scripts to validate that new system deployments, CRM updates, or database schema enhancements do not disrupt compensation tables.

Governance, Controls & SOX Compliance

  • Implement technical change control processes for database objects, maintaining version-controlled code repositories (Git) for all production scripts and schemas.
  • Ensure all database tables and pipelines adhere strictly to internal SOX-compliance protocols, maintaining automated lineage tracking and immutable audit logs.
  • Document detailed technical architecture specifications, entity-relationship diagrams (ERDs), and data dictionary definitions.

What We’re Looking For:

  • Experience: 4–7+ years of hands-on technical experience in database development, data engineering, financial systems, or complex sales compensation systems.
  • SQL Mastery: Advanced proficiency in SQL (writing complex joins, CTEs, window functions, stored procedures, dynamic SQL, and query tuning).
  • Scripting & Automation: Strong practical experience in Python (Pandas/SQLAlchemy) or Alteryx for automated data transformations and pipeline builds.
  • Data Warehousing: Experience working with enterprise cloud data warehouses (e.g., Snowflake, Google BigQuery, AWS Redshift, or Microsoft Azure Synapse).
  • Cross-Functional Collaboration: Demonstrated ability to liaise effectively with IT, Data Engineering, and Finance stakeholders to drive technical requirements.
  • Commercial Deal Translation: Ability to interpret complex commercial deal structures, including joint/split deals and strategic accounts, and translate them into clean, structured, repeatable data frameworks for system processing.

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