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Sr Sales Incentive Compensation (SIC)

ePace Technologies, IncNew York, NY🇺🇸United StatesPosted 24 Aug 2026

Why This Role Stands Out

This role offers a fantastic opportunity to leverage your Databricks and Python/Scala expertise to build impactful data solutions for sales incentive compensation at a leading technology company. If you excel at translating complex business logic into scalable data pipelines and thrive in a collaborative, on-site environment, this long-term contract position is an excellent next step in your career. Apply today to shape critical sales operations and drive data-driven success.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
New York, NY, United States
Posted
2 weeks ago
Stakeholder Management

Job Description

Sr Sales Incentive Compensation (SIC)  – Databricks

Location: New York, NY – Onsite
Duration: Long-Term Contract

We are seeking a Senior SIC Data Engineer with strong Databricks experience to design and develop scalable data solutions supporting sales incentive compensation, analytics, reporting, and enterprise data pipelines.

Key Requirements

  •  Data Engineering experience with Databricks.
  • Strong hands-on experience with Databricks, Delta Lake, DLT, Unity Catalog, and Workflows.
  • Strong Python/Scala and SQL skills.
  • Experience with Sales Incentive Compensation (SIC) processes:
    • Quota management/allocation
    • Attainment calculations
    • Commission calculations
    • Payout processing & reporting
  • Ability to translate complex incentive compensation rules into scalable data pipelines.
  • Experience with Anaplan, Oracle ICM, Varicent or similar SIC platforms is a plus.
  • Strong ETL/ELT, data modeling, data ingestion, and pipeline orchestration experience.
  • Experience with Azure/AWS/Google Cloud Platform and ADF, Event Hubs, Kafka, or equivalent.
  • Strong stakeholder management, analytical, troubleshooting, and communication skills.
  • Databricks certification is a plus.


Candidates with strong Databricks + SIC experience are highly preferred.

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