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Data Engineer
Spectraforce
US
Remote

20 hours ago

Job Description

YOUR PURPOSE

The Data Engineer will own and strengthen the data foundation that powers Customer Success for Evergreen//One, our subscription offering.
This role is responsible for building and maintaining scalable data pipelines, improving and restructuring Snowflake architecture, and ensuring subscription data is clean, trusted, and analytics-ready. You will play a critical role in resolving recurring data inconsistencies surfaced in Gainsight and Tableau by developing well-modeled, reliable datasets that serve as a clear source of truth.

This is a hands-on role focused on data ownership, modeling, quality, and performance — enabling scalable automation and future AI-driven solutions across Customer Success.
 

WHAT YOU’LL DO

  • Design, build, and maintain ETL/ELT pipelines from Salesforce, Gainsight, and other operational systems into Snowflake.
  • Audit, normalize, and restructure existing Snowflake tables and views to improve clarity, consistency, and performance.
  • Develop clean, analytics-ready data models that power Tableau dashboards, Gainsight workflows, and executive reporting.
  • Translate business logic (ARR, renewals, churn, consumption, health scoring) into structured, documented data definitions.
  • Investigate and resolve root causes of reported data discrepancies and implement durable fixes.
  • Optimize query performance, warehouse utilization, and overall Snowflake efficiency.
  • Implement data validation, monitoring, and quality controls to improve trust in reporting.
  • Document data lineage, transformations, and definitions to improve transparency and governance.
  • Partner closely with Senior Data Analysts, Customer Success, and Ops to ensure scalable, reusable datasets.
  • Prepare structured datasets that support automation initiatives and future AI use cases.
     
 

WHAT YOU’LL BRING

Minimum Required Experience & Skills

  • Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or equivalent practical experience
  • 2+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala or others.)
  • 2+ years of experience in designing, developing, and maintaining robust data models from structured and unstructured sources
  • Experience proactively identifying opportunities to improve ETL & dashboard performance and cost
  • 2+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, analytics engineer, or similar positions
  • Experience with data warehouse technologies (Snowflake, BigQuery, Spark, etc) and data build tools such as DBT.
  • Experience in Git/GitHub and branching methodologies, code review tools, CI tools, JIRA, Confluence.
  • Strong understanding of data modeling principles (normalization, dimensional modeling, schema design).
  • Experience proactively identifying and improving data pipeline or dashboard performance.
  • Strong analytical and problem-solving skills, including experience investigating and resolving data inconsistencies.
 
 Nice to have
  • Experience working with Salesforce data models (Accounts, Opportunities, Contracts, Subscriptions).
  • Experience with Gainsight, Tableau, and SnapLogic.
  • Experience supporting SaaS or subscription-based business models (ARR, renewals, consumption).
  • Exposure to automation, predictive modeling, or AI-related data preparation.
  • Experience implementing data governance, access controls, and documentation standards.
  • Experience with server-side languages like TypeScript/Node.JS/Python/Kotlin
  • Experience with RESTful API design

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