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As the Founding Software Engineer on our Data Platform team at Arlo, you will build the foundation for our ML-driven health insurance quoting system. You'll design and implement the entire data infrastructure that powers our core product, working at the intersection of data engineering and machine learning operations.
Job Responsibility:
Design and build scalable data pipelines that process billions of healthcare claims records
Develop robust ETL workflows to ingest, normalize, and transform medical data from multiple sources
Create infrastructure for real-time ML inference serving hundreds of millions of predictions
Build developer tooling to accelerate the work of our data scientists and ML engineers
Architect and implement monitoring systems to ensure data quality and model performance
Optimize PySpark code for feature construction to improve performance and efficiency
Requirements:
3+ years of experience as a backend engineer, data engineer, or software engineer with exposure to data pipelines and large-scale infrastructure
Strong understanding of data structures, algorithms, and scalable system design
Demonstrated ability to design secure, robust, and scalable infrastructure for data and backend systems
Hands-on experience with big data tools (e.g., Spark) and pipeline orchestration platforms (e.g., Dagster, Airflow, Prefect)
Proficiency in a backend programming language like Python and solid SQL skills for querying and database design
Familiarity with cloud platforms (AWS, GCP, or Azure) and their data services