Senior/Staff Data Engineer

Horizon3 · Remote · US, Remote ·
Fully remoteFull-timeSenior5+ years
COMPENSATION
€•• – ••k
0 applicants so far

Listed on the employer's job board (Ashby)

  • Senior/Staff level
  • Remote or Hybrid
  • AWS + Databricks
  • Python + SQL
  • $199k-$270k base

Join Horizon3 to design and maintain business-critical data pipelines and infrastructure for the NodeZero autonomous pentesting platform. You will expand the current data setup into a globally deployed system spanning warehousing, orchestration, and business intelligence across multiple regions.

What you'll do

  • Design and maintain data ingestion pipelines using AWS Glue and Spark
  • Build core data infrastructure including warehouse and orchestration layers
  • Evaluate warehouse strategies such as lakehouse platforms like Databricks
  • Define batch or event-driven contracts between producer and consumer teams
  • Design and evolve warehouse schemas and data models
  • Implement observability into pipelines and platform components
  • Drive collaboration across teams to own outcomes end to end

What you'll need

  • 7+ years of experience in data, infrastructure, or backend engineering
  • Strong software engineering fundamentals and clean coding practices
  • Deep understanding of distributed systems and data architecture
  • Fluent SQL skills and strong data-modeling capabilities
  • Experience owning production data infrastructure end to end
  • Bachelor’s degree in Computer Science or equivalent practical experience

Stack

  • AWS Glue
  • Databricks
  • Snowflake
  • Spark
  • Tableau
  • SQL
  • Python
  • Apache Airflow
  • Dagster

How you'll work

  • Remote or hybrid work model depending on location
  • Some roles may require presence in Chicago office
  • Global deployment across multiple regions

What you get

  • Base salary range $199,000 to $270,000 annually
  • Equity package in the form of stock options
  • Health, vision, and dental insurance for family
  • Flexible vacation policy
  • Generous parental leave