About Adversus

Adversus helps sales teams reach the right prospects through smarter outbound workflows and better calling. In RevOps, we turn data and sales insights into an engine that consistently produces high-quality leads and prioritizes the right outreach at the right time.

The Role

We’re hiring a Growth Data Engineer to build on and improve our existing lead intelligence setup. You’ll work closely with RevOps and Sales to expand our trigger/signal coverage, improve ICP matching, increase enrichment quality, and continuously refine scoring and lead routing based on real performance and conversation insights.

This role is highly hands-on: you’ll ship production data pipelines, improve reliability, and accelerate the feedback loop from outreach → results → better targeting.

What You’ll Do

• Scale signal & trigger pipelines: Identify and operationalize triggers for outreach (e.g., hiring, tech changes, intent, funding), using scraping, APIs, and data vendors.

• ICP matching & account discovery: Improve how we find and qualify companies that match our ICP across segments and markets.

• Enrichment & identity resolution: Enrich accounts with relevant contacts and verified contact details; improve matching, deduplication, and data freshness.

• Optimize lead flow using insights: Use sales outcomes and conversation insights to refine lead routing, sequencing, and messaging inputs.

• Scoring & prioritization: Maintain and evolve lead scoring—from pragmatic rules to ML-based ranking where it adds clear value.

• Production-grade pipelines: Improve observability, retries, SLAs, and data quality checks so lead delivery is reliable and measurable.

  
  

Tech Environment

You’ll work in a stack built for scale and iteration:

• Postgres

• ETL/Orchestration: Airbyte + Airflow

• Infrastructure: Google Kubernetes Engine (GKE)

• LLMs for automation and insight extraction

• Workflow automation tools (we also use n8n)

• Interest in emerging tooling (e.g., Claude Code / MCP) is a plus

  
  

What We’re Looking For

• Strong experience building and operating data pipelines in production (Python + SQL)

• Hands-on experience with APIs, scraping, and/or external data vendors (rate limits, normalization, monitoring)

• Comfortable working with Postgres and orchestrators like Airflow (and/or Airbyte)

• Practical understanding of data quality: matching, deduplication, freshness, and “trustworthy” outputs for commercial teams

• Ability to translate business needs into robust systems (RevOps/Sales context is a big plus)

• Bonus: experience with ML ranking/classification, and/or LLM-powered enrichment/insight extraction

  
  

How You’ll Be Measured

• Increased volume of ICP-matching accounts and usable enriched contacts

• Higher conversion from lead → meeting/pipeline (quality over raw volume)

• Faster iteration cycle from insight → improved targeting/scoring

• Reliability: fewer pipeline failures, better monitoring, fewer “silent data issues”

  
  

Why Adversus

• Direct impact on revenue outcomes

• Modern stack (GKE, Airflow/Airbyte, Postgres, LLMs) with room to experiment

• Close collaboration with RevOps and Sales — you’ll see the impact of your work quickly