Software Engineer, Analytics Platform
Build and enhance analytics platform features using Airflow, AWS EMR, and DuckDB for processing petabyte-scale data. Requires 4+ years software engineering experience, strong Python skills, and expertise in large-scale data systems like Spark.
Responsibilities
- Develop features for the schedule-based processing framework built on top of Airflow, AWS EMR, and DuckDB.
- Improve the stability, performance, and scalability of our data ingestion and processing platforms as we scale our geofence and robotaxi deployment.
- Collaborate with cross-functional teams, such as software engineers, data scientists, data engineers, and TPMs, to gather requirements, design robust architectures, and implement effective solutions.
- Partner with Staff and Senior engineers inside and outside the organization to translate user pain points into concrete technical solutions and roadmap items.
- Enhance system observability by building monitoring and alerting tools to track performance and measure success.
Qualifications
- Bachelor's or Master's in Computer Science or related fields with 4+ years of industry experience in software engineering
- Strong background in Python for large-scale data processing
- Familiarity with large-scale data processing systems like Spark, Trino, and DuckDB
- Experience in using cloud services, such as AWS, GCP, or Azure
- Strong experience in troubleshooting data pipeline failures and optimizing pipeline performance and cost efficiency
Staff Data Platform Engineer
Staff Data Platform Engineer building and leading AWS-native data platform architecture, orchestration, governance, and AI-readiness for analytics and ML workloads. Requires 8-10+ years experience with AWS data systems and strong technical leadership.
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Lead and mentor a team of data engineers building scalable data pipelines and platform infrastructure. Hands-on coding, operational excellence, and cross-functional collaboration with analytics, data science, and business teams.
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