Data Engineering Lead – Data Quality Systems

🕒 September 2

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 28%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Lead a small team of 3–5 Applied AI Engineers • Design and build verification, sampling, and scoring pipelines across billions of company and people records in 13 markets • Build quality-check frameworks, harnesses, abstractions, and SKILL.md specifications • Develop eval harnesses for LLM-based validation and extraction • Create labelled evaluation sets and track precision and recall • Calibrate judges, version prompts, and detect drift in vendor model updates • Implement pre- and post-production release gates to block bad data • Build failure-analysis and triage tooling • Root-cause quality incidents at scale, ship fixes, and convert failures into permanent automated checks • Provide technical direction, conduct code reviews, pair with engineers, and develop team members • Write complex production code and unblock engineers building on the frameworks

🎯 Requirements

• 7+ years building production data systems in business-critical environments • Experience working with billions of rows • Experience building data quality systems and frameworks, including validation engines, anomaly detection, scoring, sampling strategies, and reconciliation against ground truth • Experience designing eval or test harnesses that other engineers depend on • Experience technically leading a small team while remaining hands-on • Strong Python and advanced SQL skills • Production experience operating LLMs with eval sets, versioned prompts, logged traces, cost ceilings, and precision/recall debugging • Experience shipping real work with agentic IDEs such as Claude Code, Cursor, or equivalent • Strong judgment on deterministic rules versus LLM-based checks • Highly valued: B2B data experience, cloud data platforms, AWS, Airflow or equivalent, vector databases, embeddings, retrieval patterns, and startup or scaleup experience

🏖️ Benefits

• Competitive base + meaningful equity • Flexible working: no fixed hours • Fully remote work • Equal opportunity employer • Small senior teams with minimal process • Weekly releases moving toward daily • Teams own their stack end to end