Data Engineer

🔥 18 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 13%

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 and run pipelines that turn raw records into datasets used by Firmable's product and agents • Implement SQL, dbt, Airflow, and Snowflake data pipelines • Integrate LLM extraction, enrichment, and matching steps into pipelines processing millions of records per day • Create structured outputs, retries, and human-review paths for model workflows • Build evaluation sets and regression tests to measure model-step accuracy • Route simple decisions to lower-cost models and complex tasks to stronger LLMs • Track token costs per pipeline • Deduplicate company and people records across covered markets • Build self-recovering Airflow DAGs and budget-conscious Snowflake models • Use coding agents such as Claude Code, focusing engineering time on design, review, and evaluations • Log every LLM call with prompt version, model, and cost • Ship improvements through weekly releases moving toward daily releases

🎯 Requirements

• 3–5 years in data engineering • Strong Python and SQL • Production dbt and Airflow experience • Experience with a cloud warehouse; Snowflake preferred • Nice to have: Logfire or OpenTelemetry • Nice to have: embeddings or fuzzy matching for entity resolution • Nice to have: fine-tuning small models • Nice to have: AWS and PostgreSQL • Nice to have: Spark or streaming • Nice to have: GDPR/SOC2 • Experience with LLM extraction, enrichment, and matching at production scale is implied by the role context • Ability to use AI coding tools daily and show work shipped with them • Production pipeline ownership, including fixing failures • Experience working with millions or billions of records rather than only thousands of rows • Experience building pipelines in code rather than only drag-and-drop ETL tools • Ability to work independently without detailed specifications, fixed hours, or close supervision

🏖️ Benefits

• Competitive base and meaningful equity • Fully remote work arrangement • Equal opportunity employer