Senior / Staff Data Platform Engineer
Builds and modernizes data platform infrastructure handling billions of API calls using tools like Kinesis, S3, Athena, and Airflow. Collaborates with customers to incorporate feedback and requires experience with data stacks including Snowflake or Databricks.
Responsibilities
- Work on core Radar data infrastructure built with Kinesis, S3, Athena, Terraform, Airflow, Parquet, Metabase, Python, Redis, and MongoDB (some of these need to be replaced - you'll help figure out what that looks like).
- Improve our current data platform via incremental improvements and deploying next generation infra to level up our stack.
- Talk to Radar customers and prospects, hear their feedback, incorporate it into your work and make them successful.
Requirements
- Have experience building data infrastructure.
- Besides experience with some of our current data stack, have experience with several of Snowflake, Clickhouse, Databricks, Dynamo and dbt or similar tools.
- Are interested in talking to customers or prospects and making them successful.
- Are deeply curious about how things work, and have the tenacity to sit with hard problems and power through them.
Nice-to-haves
- Are a former technical co-founder.
- Have experience building end-to-end customer facing analytics, real-time streaming solutions, leveraging cold and hot storage to achieve product goals.
Compensation
- Base salary range: $200,000 - $300,000/year.
- Opportunity for performance bonuses and incentives.
- Stock option grants.
- 401(k) with 4% match.
- Health, dental, vision insurance (100% coverage).
- Unlimited PTO, 12 weeks paid parental leave, commuter/fitness benefits.
Staff Engineer - Data Platform
Staff-level technical lead and architect for Haus's data ingestion and normalization platform. Owns schema evolution, data contracts, DQ frameworks, lineage, and pipeline observability in a GCP/BigQuery/dbt stack. Partners with DS and Product teams.
Senior Software Engineer
Senior Software Engineer building and scaling Chime's data platform, ETL pipelines, and distributed data infrastructure. Requires a Master's degree and 3+ years of experience with AWS/GCP, Spark/Trino, Kubernetes, and CI/CD.
Data Engineer, Machine Learning
Build and maintain production data pipelines that prepare conversational, voice, and multimodal data for ML model training and evaluation. Partner closely with ML engineers to deliver high-quality, versioned datasets and infrastructure.