Senior Data Engineer – Data Platform

🕒 September 2

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 48%

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

• Architect the transformation and warehouse layer that turns billions of raw records into an accurate B2B dataset • Design production architecture for LLM-based extraction, enrichment, entity resolution, and semantic validation • Define model design, materialisation, warehouse cost and performance, orchestration patterns, and rule-versus-LLM standards • Create reusable reference implementations for the engineering team • Design eval harnesses, labelled sets, scorers, judge calibration, and regression suites • Own precision and recall targets for quality checks • Establish token budgets, model routing, drift detection, and cost controls • Implement observability for LLM calls, including prompt version, model, cost, latency, and decision logging • Build dbt transformation layers with business logic and optimise Snowflake performance, clustering, materialisation, and cost • Establish Airflow orchestration patterns for recovery and cost-aware scheduling • Build AWS infrastructure as code • Develop embeddings and retrieval patterns for company and people entity resolution across 13 markets • Provide technical direction in architecture decisions with sourcing, data quality, product, and analytics teams

🎯 Requirements

• 5+ years building production data platforms in business-critical environments • Architecture owned end to end • 2+ years of experience with Snowflake • Experience working with billions of rows • Experience shipping LLMs inside data pipelines as production systems • Experience with structured outputs, versioned prompts, and labelled eval sets • Experience designing eval harnesses, scorers, labelled sets, judge calibration, and regression suites • Strong judgment on rules versus LLMs • Expert Python and SQL skills • Expert dbt and Snowflake skills, including warehouse design, query optimisation, clustering, RBAC, and cost management at scale • Extensive production Airflow experience, including orchestration, dependency management, recovery patterns, and cost optimisation • Solid AWS experience with S3, Lambda, Glue, ECS, and RDS • Daily use of AI coding tools such as Claude Code, Cursor, or equivalent, with shipped work to show • Architecture judgment and product mindset • Experience with eval frameworks such as Braintrust, Promptfoo, or Inspect is highly valued • Experience with LLM tracing such as Logfire or OpenTelemetry is highly valued • Experience with embeddings, vector search, or fuzzy matching for entity resolution at scale is highly valued • Experience fine-tuning or distilling small models is highly valued • Experience with dbt Cloud and CI/CD for data pipelines is highly valued • Experience with Spark or PySpark and streaming technologies such as Kafka, Kinesis, or Snowpipe Streaming is highly valued • Experience with B2B data, including firmographics, people data, and company registries, is highly valued • Knowledge of data privacy and compliance, including GDPR, SOC2, and CCPA, is highly valued

🏖️ Benefits

• Competitive base salary • Meaningful equity • AI-native working environment with AI coding tools, automated testing, and AI-assisted review • No fixed hours • Small senior teams with minimal process • Weekly releases moving toward daily releases • End-to-end ownership of the stack