Data Engineer
What you'll do:
Build and maintain reliable data pipelines and ETL/ELT workflows
Develop and optimize data models for analytics and internal tools
Work with team members to deliver clean, trusted datasets
Support core data platform tools like Spark and AWS (S3, SNS, SQS, ECS/Fargate, EMR)
Monitor data pipelines for quality, performance, and reliability
Write clear documentation and contribute to test coverage and CI/CD processes
Help shape our data lakehouse architecture and platform roadmap
What you'll bring:
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
2-4 years of experience in data engineering or a backend data-related role
Strong skills in Java, Scala, or another backend programming language
Python (PySpark/pandas) skills
Experience with SQL and distributed data systems (e.g., Spark, Kafka, SQS)
Familiarity with NoSQL stores like Cassandra, HBase, or similar
Understanding of data modeling for analytics and reporting
Proficient in English with strong communication skills - able to explain or demo work to non-engineers
Self-driven - picks up new technologies and frameworks with little guidance
Debugs methodically; breaks complex problems into smaller steps
Open to feedback - iterates and improves through code reviews
Uses AI-assisted engineering tools (Claude Code, Codex, Cursor, etc.) as part of daily workflow
Reliable internet connection to sustain video, audio, and screen sharing
It'd be great if you had:
Experience with dbt, Databricks, or real-time data pipelines
Familiarity with cloud infrastructure tools like Terraform or CloudFormation
Interest in data governance, ML pipelines, or compliance standards
Personal projects or open source contributions demonstrating initiative
Why you'll love working here:
Work on data that supports meaningful software security outcomes
Modern tools in a cloud-first, open-source-friendly environment
A team that values clarity, learning, and autonomy