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About the Role
As a Staff Python Engineer, you will be a technical leader in our Data Science Products team, ingesting billions of complex sensor data points daily to produce advanced machine learning products. You will influence technical strategy, promote best practices, and design, build, and scale data services and architectures.
Responsibilities
- Own the technical roadmap for Spark-based data processes to ensure Airflow pipelines are performant, cost-effective, and scalable.
- Enhance existing services through hands-on development and solve complex performance bottlenecks, concurrency issues, and systemic bugs.
- Define standards for efficient, testable, and reusable Python code across the organization.
- Partner with Data Scientists to translate modeling requirements into high-performance production services.
- Design data architectures and pipeline designs with downstream latency, freshness, and reliability in mind.
- Evolve infrastructure-as-code (AWS) and CI/CD pipelines.
- Contribute to automation and observability patterns for high-confidence deployments with zero downtime.
- Lead hands-on development of platform enhancements, such as establishing feature stores for machine learning and building automated data monitoring systems.
- Lead the adoption of AI throughout the software development lifecycle, evolving internal coding practices.
Requirements
- Extensive history of building and scaling data-intensive applications in production.
- Track record of leading technical initiatives from conception to deployment.
- Expert-level Python and its data ecosystem (Numpy, Pandas), including designing frameworks for data tasks.
- Deep understanding of distributed data processing engines like Apache Spark.
- Ability to reason about the full data lifecycle from ingestion through to real-time serving.
- System designs must meet downstream API performance and data freshness requirements.
- Strong command of Linux, containers (Docker), and infrastructure as code for cloud deployments (AWS preferred).
- Passion for elevating engineering standards through pair programming and detailed code reviews.
Skills
- Python
- Distributed systems
- Spark
- Airflow
- AWS
- Linux
- Docker
- Infrastructure as Code
- CI/CD
- Machine Learning
- Data Science
- Numpy
- Pandas
Location
- Global
Work Type
- Full-time
Experience Level
- Staff
- Senior
About the Company
- Arrive is a leading global mobility platform, including brands like EasyPark, Flowbird, RingGo, ParkMobile and Parkopedia.
- Present in over 90 countries and 20,000 cities, Arrive helps people and decision-makers make smarter decisions about urban mobility and ease the experience of travel worldwide.
- Parkopedia is the world’s leading connected car services provider, used by millions of drivers and organisations such as Apple, Here, TomTom, and 20 automotive brands.
- Parkopedia's mission is to provide the best in-car data and transaction services, to make mobility ecological, efficient and convenient.