Firmable is the market-leading B2B sales intelligence platform in Asia-Pacific. Our competitive moat is our data: the deepest, most localised company and people dataset in every market we operate in. We've proven the model in ANZ. Now we're scaling it across Southeast Asia and the US.
Every record Firmable sells starts in a sourcing pipeline. This role architects that pipeline.
The Role
Lead Data Engineer: Sourcing designs and owns the end-to-end extraction and ETL pipeline that turns unstructured web data into the world's most accurate B2B dataset across 13 markets. You set the architectural standards: extractor patterns, proxy strategy, LLM infrastructure as production systems, agentic escalation workflows, and cost-aware orchestration.
This is not a pipeline maintenance or incremental optimisation role. You're architecting the framework other engineers ship into, building for the hardest extraction problems (anti-bot defences, JS-heavy rendering, schema drift), and owning the sourcing layer end to end.
~80% hands-on architecture and reference implementation:



designing extractor frameworks, shipping the hardest extractors, building agentic pipelines, writing eval harnesses and labelled datasets. ~20% cross-functional voice: technical input on sourcing decisions with data platform, product, and analytics; setting standards for coverage, schema, and accuracy.
What You'll Own
Sourcing and ETL architecture
• End-to-end pipeline design: extraction, normalisation, deduplication, validation, and load; plus cost, performance, and reliability of the whole layer

• Sourcing layer standards: coverage, accuracy, schema design; the rule-vs-LLM standard codified so the team applies it without you

• Cost and performance optimisation: cost ceilings with the token math behind them, incremental processing, recovery design, scheduling

Extraction systems and frameworks
• Extractor framework: patterns, abstractions, and tooling other engineers ship into; new extractors are rapid to b

📌 Lead Data Engineer (India)
🏢 Firmable
📍 India