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

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

Highest-signal resume keywords

SQL SkillsPython ProficiencyExperience With DatabricksCloud Platform Experience (GCP Preferred)Analytics Engineering Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonPySparkDatabricksData ModelingData Pipeline DevelopmentAutomated Client Health ScoringVersion ControlCI/CDExcel

Soft Skills

Strong Written EnglishClear Documentation Skills

Tools & Technologies

SalesforceDatabricksGCPAI Coding Assistants

Industry Keywords

Analytics EngineeringData EngineeringClient 360 ViewCustomer SuccessRenewal Risk

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
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 and ability to clearly document technical work
Willingness to work under an Independent Contractor Agreement and be responsible for own taxes and benefits
Must be currently residing in and legally authorized to work in either Indonesia or Vietnam
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
Work from home
Equal opportunity employer
Disability accommodations available during the interview process