gomotive logo

Sales Data Quality Analyst

gomotive Pakistan - Remote


No Relocation

Posted: August 6, 2026

Job Description

What You'll Do:

  • Design and refine deduplication logic for complex scenarios (e.g., parent-child, multi-segment).
  • Use SQL and Python to automate deduplication and reporting processes.
  • Integrate AI tools (Gemini, Google AI Studio, Perplexity, Glean) for predictive duplicate detection and prevention.
  • Build and maintain real-time dashboards for deduplication metrics and business impact.
  • Collaborate with Engineering and Systems teams to enhance deduplication pipelines.
  • Document best practices and lead training sessions for Sales and Operations.
  • Provide actionable insights and recommendations to business stakeholders.
  • Identify and merge duplicate accounts/contacts by analyzing multiple data scenarios through DemandTool and Python script.
  • Analyze large datasets of accounts/contacts/leads leveraging Snowflake to develop insights and recommendations for improving sales performance by highlighting the gaps in the data for deduplication.
  • Create and maintain data models (using Snowflake) and dashboards (Salesforce & Tableau) to track key metrics and provide actionable insights for deduplication.
  • Apply AI/ML techniques to search web information, identify, classify, and resolve data issues (e.g., outliers, missing data, duplicates).
  • Help drive analytical reporting, including monthly business reviews, deep dives, and ad hoc analysis requests.
  • Publish process documentation on platforms such as Seismic and Confluence.
  • Work on ad-hoc projects as requested by stakeholders.
  • Deal with different sorts of accounts including Franchise, partner, and contractor accounts for deduplication needs.
  • Ability to find gaps for process improvement, propose solutions, and implement them.

What We're Looking For:

  • Proactive problem-solving: Taking initiative to improve data quality.
  • Collaboration: Working closely with stakeholders across teams.
  • Accountability: Owning the accuracy and integrity of data.
  • Continuous improvement: Seeking ways to optimize deduplication strategies.
  • Customer-centric mindset: Understanding how data quality impacts sales performance.



Additional Content

What You'll Do:

  • Design and refine deduplication logic for complex scenarios (e.g., parent-child, multi-segment).
  • Use SQL and Python to automate deduplication and reporting processes.
  • Integrate AI tools (Gemini, Google AI Studio, Perplexity, Glean) for predictive duplicate detection and prevention.
  • Build and maintain real-time dashboards for deduplication metrics and business impact.
  • Collaborate with Engineering and Systems teams to enhance deduplication pipelines.
  • Document best practices and lead training sessions for Sales and Operations.
  • Provide actionable insights and recommendations to business stakeholders.
  • Identify and merge duplicate accounts/contacts by analyzing multiple data scenarios through DemandTool and Python script.
  • Analyze large datasets of accounts/contacts/leads leveraging Snowflake to develop insights and recommendations for improving sales performance by highlighting the gaps in the data for deduplication.
  • Create and maintain data models (using Snowflake) and dashboards (Salesforce & Tableau) to track key metrics and provide actionable insights for deduplication.
  • Apply AI/ML techniques to search web information, identify, classify, and resolve data issues (e.g., outliers, missing data, duplicates).
  • Help drive analytical reporting, including monthly business reviews, deep dives, and ad hoc analysis requests.
  • Publish process documentation on platforms such as Seismic and Confluence.
  • Work on ad-hoc projects as requested by stakeholders.
  • Deal with different sorts of accounts including Franchise, partner, and contractor accounts for deduplication needs.
  • Ability to find gaps for process improvement, propose solutions, and implement them.

What We're Looking For:

  • Proactive problem-solving: Taking initiative to improve data quality.
  • Collaboration: Working closely with stakeholders across teams.
  • Accountability: Owning the accuracy and integrity of data.
  • Continuous improvement: Seeking ways to optimize deduplication strategies.
  • Customer-centric mindset: Understanding how data quality impacts sales performance.