Data Automation Engineer

Highlights :

• Position Title: Data Automation Engineer
  

• Exp: 2+ years
  

• Job Location: Remote
  

About the Role

We're looking for a Data Automation Engineer who is strong in data analysis and can build and manage automated data systems end-to-end. You'll connect marketing and business platforms, automate data flow between them, and use that data to generate insights that support business decisions. You should be able to understand business problems, solve them independently, and explain your automation work clearly to non-technical clients.

Key Responsibilities

• Understand business problems first, then design and build automation workflows that solve them end-to-end, working independently as an individual contributor.
  

• Analyzing data from connected platforms to generate insights and support business decisions is the core focus of the role.
  

• Build and maintain automated workflows using tools like Zapier, Make.com, or similar, connecting different systems and data sources through connectors and integrations.
  

• Own the ETL process - extract, clean, standardise, and load data into a central database.
  

• Use AI tools like Claude Code to support automation and data workflow tasks.
  

• Maintain and improve the overall data setup as data volume and business requirements grow.
  

• Clearly explain automation logic, workflows, and problem-solving approaches to non-technical clients and stakeholders.
  

Must-Have Requirements

• Minimum 2 yrs of hands-on experience with automation tools like Zapier, Make.com, or similar, including setting up connectors and integrations between different platforms.
  

• Proven experience effectively using connectors to link different tools and systems together, with a track record of having built such integrations in day-to-day work.
  

• Good working knowledge of the ETL process - extracting, cleaning, standardising, and loading data.
  

• Hands-on, proven experience using Claude Code.
  

• Working knowledge of databases such as Supabase, PostgreSQL, BigQuery, or Snowflake.
  

• Basic understanding of marketing data (e.g., Google Ads, Meta Ads metrics) as a general example of the type of data you may work with.
  

• Able to independently understand business problems and translate them into automated solutions, explaining the work clearly to non-technical clients.