Data Engineer – Data Platform

🕒 September 3

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 47%

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

• Build LLM-in-the-pipeline systems for extraction, enrichment, entity resolution, and semantic validation over millions of records daily • Build labelled evaluation sets, scorers, and regression suites for prompt and model changes • Implement deterministic checks, dbt tests, data contracts, and SQL where appropriate • Implement model routing, token budgets, cost controls, and drift detection • Log LLM prompts, versions, models, costs, latency, and decisions • Own Airflow orchestration, dbt models, Snowflake performance and cost, and AWS infrastructure as code • Develop matching and deduplication systems using embeddings and retrieval patterns across 13 markets • Own data reliability, cost, and downstream data trust for product, analytics, and AI systems

🎯 Requirements

• 3+ years in data engineering or data infrastructure • 2+ years of experience with Snowflake • Strong Python and SQL skills, production-grade and performance-aware at very large scale • Production experience shipping LLMs inside data pipelines, with structured outputs and a labelled eval set • Experience building or maintaining LLM evaluation or test harnesses • Judgement in choosing deterministic rules versus LLMs • Production dbt and Airflow experience • Cloud warehouse experience; Snowflake preferred • Experience with AI coding tools such as Claude Code, Cursor, or equivalent, used daily with shipped work • Ownership and systems thinking • Experience with eval frameworks and LLM tracing is highly valued • Experience with embeddings, vector search, or fuzzy matching for entity resolution is highly valued • Experience fine-tuning or distilling small models is highly valued • AWS at scale (S3, Lambda, Glue, ECS, RDS) and PostgreSQL is highly valued • Spark or PySpark and streaming technologies (Kafka, Kinesis, Snowpipe Streaming) are highly valued • Data privacy and compliance knowledge (GDPR, SOC2, CCPA) is highly valued

🏖️ Benefits

• Competitive base salary • Meaningful equity • Flexible working with no fixed hours