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. Responsibilities • 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. Qualifications • 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 Compensation: $45 - $60 per hour ID: 37237912