AI / Data Marketing · 2023–2024
Facebook Marketing Data Pipeline
Orcawise · Greater London
01
Problem
Marketing and competitive intelligence teams needed reliable extraction of platform signals without brittle, one-off scrapers.
02
Challenge
Design a modular ETL automation tool that minimized latency, respected privacy constraints, and could be maintained by a distributed engineering team.
03
Solution
Architected and co-built a web automation pipeline for extract–transform–load from Facebook, with documentation, optimization passes, and security-conscious handling of user-related data.
04
Impact
Enabled faster market analysis cycles and cleaner data inputs for AI / data marketing workflows, maintained by a distributed engineering team after handoff.
Approach
- 01
Mapped the data sources and fields required for AI / data marketing workflows before writing any extraction code.
- 02
Designed a modular ETL architecture that separated extraction, transformation, and load stages for independent testing and maintenance.
- 03
Built privacy and security safeguards around user-related data into the pipeline from the outset, not layered on afterward.
- 04
Produced technical documentation and regular extraction reports to support market-analysis and competitive-intelligence decisions.
Outcomes
- Modular, documented ETL pipeline maintainable by a distributed engineering team
- Reduced extraction latency through targeted optimization passes
- Compliance-conscious handling of user-related data throughout
- Faster, cleaner inputs feeding downstream AI / data marketing analysis