Data Engineer - Customer Success Analytics

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.

• 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.

• 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, Big Query, Spark, etc) and data build tools such as DBT.
• Experience in Git/Git Hub 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.

• Experience working with Salesforce data models (Accounts, Opportunities, Contracts, Subscriptions).
• Experience with Gainsight, Tableau, and Snap Logic.
• 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 Type Script/Node.
  
  JS/Python/Kotlin.
• Experience with RESTful API design.

Compensation: $45 - $60 per hour

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