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Paystone

Analytics Engineer

Paystone

. Build and maintain reliable data pipelines and models across Salesforce, transaction, product, onboarding, renewal, pricing and support data .

Posted 11/11/2026full-timeRemote • Indonesia, VietnamJuniorMid-LevelWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining data pipelines and models, with strong proficiency in SQL, Python, and Databricks. Capable of delivering actionable insights and metrics to support customer success and business decision-making.

Highest-signal resume keywords
SQL SkillsPython ProficiencyDatabricks ExperienceAnalytics EngineeringSalesforce Data Models

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
SQLPythonPySparkDatabricksAI Coding AssistantsExcelAnalytics EngineeringData EngineeringVersion ControlCI/CD
Soft Skills
Strong Written EnglishDocumentation Skills
Tools & Technologies
GCPSalesforceDataCandyDeltaJobsWorkflowsDbt
Industry Keywords
SaaS RetentionCustomer Health MetricsB2B SaaSClient 360 ViewGoverned Datasets

Tech Stack

Tools & technologies
CloudGoogle Cloud PlatformPySparkPythonSQL

About the role

Key responsibilities & impact
  • Build and maintain reliable data pipelines and models across Salesforce, transaction, product, onboarding, renewal, pricing and support data
  • Develop and maintain a governed Client 360 view connecting accounts, locations, products, commercial terms, adoption and revenue performance
  • Define and document trusted metrics for GRR, NRR, churn, client health, time-to-value and renewal risk
  • Develop automated client health scoring and renewal-risk triggers across the customer portfolio
  • Surface clear, actionable client insights in Salesforce for Customer Success and Account Management teams
  • Prepare governed, high-quality datasets to support AI and agentic workflows
  • Establish and own DataCandy’s customer data foundation
  • Centralize product, client, commercial and lifecycle data in Databricks
  • Develop consistent business metrics and surface insights that help teams identify opportunities, risks and priorities
  • Design scalable solutions, automate manual processes and create data products supporting business decision-making

Requirements

What you’ll need
  • 2–4+ years of experience in analytics engineering, data engineering or a related field
  • Strong SQL skills
  • Solid working knowledge of Python
  • Hands-on experience with PySpark and Databricks, including Delta, Jobs and Workflows
  • Cloud platform experience, with GCP preferred
  • Experience with version control, code review, CI/CD and infrastructure as code
  • Practical experience using AI coding assistants and agentic workflows
  • Strong Excel skills for ad hoc analysis and reporting
  • Strong written English
  • Ability to clearly document technical work
  • Experience with Salesforce data models, SaaS retention and customer health metrics, dbt, payments, loyalty or B2B SaaS environments is advantageous
  • Must be currently residing in and legally authorized to work in Indonesia or Vietnam
  • Willingness to work under an independent contractor agreement and be responsible for own taxes and benefits
  • Willingness and ability to work during EST business hours
  • Willingness to purchase own equipment upfront and be reimbursed later

Benefits

Comp & perks
  • Compensation tied to market data
  • Flexible Time-off
  • Career development opportunities
  • Work from home
  • Equal opportunity employer
  • Disability accommodations available during the interview process