Life360 is looking to enhance and maintain its data processing and storage pipelines/workflows to handle a massive volume of data (60 billion unique location points, 12 billion user actions, 8 billion miles driven monthly) and empower internal teams to make data-driven decisions.
Requirements
- Minimum 5+ years of experience working with high volume data infrastructure.
- Experience with Databricks, AWS, ETL and Job orchestration tooling.
- Extensive experience programming in one of the following languages: Python / Java / Scala.
- Experience in data modeling, optimizing SQL queries, and system performance tuning.
- Knowledge and proficiency in the latest open source and data frameworks, modern data platform tech stacks and tools.
- You are proficient with SQL, AWS, Databases, Apache Spark, Spark Streaming, EMR, and Kinesis/Kafka
- You delight in crushing messy unstructured data and making the world sane by producing quality data that is clean and usable
Responsibilities
- Design, implement, and manage scalable data processing platforms used for real-time analytics and exploratory data analysis.
- Manage our data from ingestion through ETL to storage and batch processing.
- Automate, test and harden all data workflows.
- Architect logical and physical data models to ensure the needs of the business are met.
- Collaborate with product analytics, data scientists, while applying best practices
- Architect and develop systems and algorithms for distributed real-time analytics and data processing
- Implement strategies for acquiring data to develop new insights
Other
- BS in Computer Science, Software Engineering, Mathematics, or equivalent experience
- Always be learning and staying up to speed with the fast moving data world.
- You have good communication skills and can work independently
- Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within Canada) regardless of any specified location above.
