Lead Data Engineer – Sourcing

🔥 2 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

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Firmable

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2023

🤝 B2B

☁️ SaaS

🤖 Artificial Intelligence

B2B • SaaS • Artificial Intelligence

Firmable is an AI-native B2B sales platform that provides company and contact data, prospect list building, automated buying-signal monitoring, and CRM enrichment. It uses LLMs and agentic AI to assemble and refresh data across hundreds of sources, surface high-intent accounts (role changes, funding, search intent, technology adoption, vertical signals), and generate CRM tasks to guide timely outreach. Firmable integrates with major CRMs (HubSpot, Salesforce, Dynamics, Pipedrive), browser extensions, and other tools, and is positioned as an alternative to legacy data providers like ZoomInfo and Apollo, targeting sales leaders, account executives, SDRs, revenue operations, marketing, and recruiters. The product is offered as a SaaS with terms aimed at smaller and mid-market teams (no enterprise-only contracts or auto-renew traps) and is used by 1,300+ businesses.

📋 Description

• Design and own the end-to-end extraction and ETL pipeline transforming unstructured web data into a B2B dataset across 13 markets • Set architectural standards for extractor patterns, proxy strategy, LLM infrastructure, agentic escalation workflows, and cost-aware orchestration • Architect frameworks and ship difficult extractors for anti-bot defences, JS-heavy rendering, schema drift, and low-quality structures • Own extraction, normalisation, deduplication, validation, loading, cost, performance, and reliability • Build rule-based triage, LLM escalation, structured-output validation, retries, and human-review queues • Develop production LLM infrastructure with versioned prompts, labelled evaluation sets, precision/recall measurement, rollback capability, tracing, and drift detection • Create eval frameworks, observability scaffolding, model-choice playbooks, and versioned SKILL.md specifications • Establish Airflow or equivalent orchestration patterns, dependency management, recovery, and cost-aware scheduling • Provide technical input to data platform, product, and analytics teams • Set standards for coverage, schema, and accuracy • Ship approximately 80% hands-on architecture and reference implementation and contribute approximately 20% cross-functionally • Architect greenfield sourcing infrastructure and own outcomes end to end

🎯 Requirements

• 6+ years shipping production extraction, ETL, or data pipeline systems in business-critical environments • Deep web extraction at scale, including anti-bot defences, proxy architecture, JS rendering, schema drift, and recovery • Experience shipping LLMs inside extraction pipelines as production systems • Structured outputs, versioned prompts, labelled eval sets, logged traces, precision/recall judges, and vendor model drift detection • Experience building agents and tool-calling pipelines • Experience architecting agent workflows and writing SKILL.md specifications • Strong judgment in choosing rules versus LLMs • Expert Python, including production-grade and concurrency-aware development • Advanced SQL for complex transformations and performance optimisation • Extensive Airflow or equivalent experience • Experience shipping with agentic IDEs such as Claude Code or Cursor • Architecture judgment and product mindset • Existing hands-on use of AI tools, structured outputs, evals, traces, and LLM tracing • Highly valued: Snowflake, Redshift, AWS Lambda, S3, ECS, Glue • Highly valued: vector databases, embeddings, and retrieval patterns • Highly valued: Braintrust, Promptfoo, Inspect, and LLM tracing tooling • Highly valued: data quality frameworks with automated testing and anomaly detection • Highly valued: B2B data experience, including firmographics, people data, and company registries • Highly valued: GDPR and CCPA knowledge • Highly valued: startup or scaleup experience • Not suitable for candidates from a pure ops or data analytics background without shipped systems engineering at scale

🏖️ Benefits

• No fixed hours • Full autonomy on architecture choices