Key Responsibilities
Build & Run the Data Pipeline (Core of this Role)
- Connect live data sources — Google Ads, Meta Ads, Facebook Ads, CRM, and internal systems — directly via APIs, replacing all manual CSV exports with automated, reliable feeds
- Own the full ETL process: extract data from multiple platforms, clean and standardise it, and load it into a central database (Supabase)
- Build and maintain automated workflows so dashboards update on their own — no manual effort needed
- Set up data quality checks and alerts so any issue in the data is caught automatically before it reaches the client
Build the Dashboards
- Build clear, structured dashboards that connect directly to live data — so numbers update automatically without anyone touching them
- Make sure every client account's data is accurate and trustworthy at all times
- Identify and fix reporting discrepancies at the source, not just on the surface
Analyse & Advise
- Read the data, spot trends and problems, and give a clear view on what is working and what is not
- Turn findings into simple, actionable recommendations that a non-technical person can understand and act on
Must-Have Requirements
- Digital Marketing Knowledge — Mandatory: Proven hands-on experience working with Google Ads, Meta Ads, and Facebook Ads data — understanding metrics like ROAS, CPA, CTR, spend, and conversions
- ETL & Workflow Automation — Mandatory: You have built real automated pipelines and workflows end-to-end, not just assisted in building them
- Automation Tools: Hands-on experience with tools like N8N, Make.com, Zoho Flow, or similar to automate data movement and remove manual steps
- Strong SQL: Daily working knowledge — joins, aggregations, data cleaning, and optimisation
- Python: For scripting, automation, and pipeline work
- Database Experience: Hands-on with Supabase, PostgreSQL, BigQuery, or Snowflake
- API Connections: Experience connecting platforms to databases using REST APIs
- Data Modeling: Ability to design clean, maintainable table structures for reporting
Nice to Have
- Prior experience working inside a digital marketing agency
- Familiarity with cloud data warehouses (BigQuery, Snowflake, Redshift)
- A portfolio of dashboards with real business outcomes they drove
Pay: ₹500,000.00 - ₹1,000,000.00 per year
Application Question(s):
- Which automation tool have you used to schedule data pipelines?
- How many years of experience do you have as a Data Engineer?
- Do you have experience with digital marketing services?
Work Location: In person
