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Medium—early-mid data role with specific digital-marketing and ETL tool requirements limiting broad applicants.
Medium—core data engineering and analytics skills transfer, but mandatory marketing platform experience increases specificity.
High—explicit 2+ years plus mandatory digital-marketing, ETL automation, SQL, and Python requirements.
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Build, operate, and own end-to-end automated ETL pipelines connecting live data sources (Google Ads, Meta Ads, CRM, internal systems) to a central database (Supabase).
Develop and maintain automated dashboards that update in real-time, ensuring data accuracy and timely anomaly detection before data reaches clients.
Analyze marketing data to identify trends and issues, delivering clear, actionable insights and recommendations to non-technical stakeholders.
Minimum 2 years work experience in data science or related role.
Mandatory hands-on experience with Google Ads, Meta Ads, Facebook Ads data and digital marketing metrics (ROAS, CPA, CTR, spend, conversions).
Proficient in ETL process including building automated pipelines, strong SQL skills, Python scripting, and API integrations.
Experience with automation tools (N8N, Make.com, Zoho Flow or similar) and databases like Supabase, PostgreSQL, BigQuery, or Snowflake.
Experienced in digital marketing data environments with ability to translate complex data into actionable insights for clients.
Comfortable designing and maintaining complex ETL workflows and real-time dashboards with automated quality controls.
Skilled in working independently on advanced automation and data engineering tasks within a small or medium-sized tech-driven team.