Data Engineer (Go to Market)

TL;DR

Data Engineer (Go to Market) (Python/Snowflake): Architecting and building robust data frameworks for Operational Data Store and Enterprise Data Lake platforms with an accent on scalable data solutions and complex transformations. Focus on designing automated workflows, implementing CI/CD pipelines, and optimizing marketing data for strategic decision-making.

Location: Remote (USA)

Salary: $85,000 - $120,000

Company

Global leader in cybersecurity redefining security with an AI-native platform to stop breaches across all industries.

What you will do

• Lead the full lifecycle of data engineering projects from requirement gathering to production deployment.
• Design and maintain complex data transformations using Python, Airflow, DBT, and Snowflake.
• Build and scale automated workflows to manage sophisticated data dependencies.
• Implement CI/CD processes and maintain high engineering standards via GitHub.
• Create automated data validation processes to ensure high accuracy and integrity.
• Partner with Analytics, Sales, and Marketing teams to build curated datasets for strategic insights.

Requirements

• 3+ years of experience in SQL, Python, DBT, and Apache Airflow.
• Deep expertise in cloud databases such as Snowflake or Redshift.
• Hands-on experience with marketing datasets, including funnel stages and revenue attribution models.
• Advanced proficiency in DBT lifecycle, custom macros, and modular project structures.
• Experience with CI/CD tools like Jenkins or GitLab CI/CD.
• Bachelor's Degree in Computer Science, IT, or equivalent experience.

Nice to have

• Knowledge of marketing automation tools: Salesforce, Marketo, People.ai, or Outreach.
• Understanding of machine learning concepts and support for feature stores.

Culture & Benefits

• Market leader compensation and equity awards.
• Comprehensive physical and mental wellness programs.
• Competitive vacation and holiday packages.
• Paid parental and adoption leaves.
• Professional development opportunities for all employees.
• Supportive culture with employee networks and geographic neighborhood groups.