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The Data Engineering team is a cross-functional team responsible for data integration, monitoring, and quality. This includes automating data flows, alerting, fetching, and checking across various stages of data transformation and projection.
Key Responsibilities
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Develop data architecture for data ingestion, validation, and processing.
Identify, design, and implement process improvements, such as automating manual tasks, optimizing data delivery, and redesigning infrastructure for enhanced scalability.
Create and maintain optimal data pipeline architecture using microservices.
Work with other members of the data team, including data architects, data analysts, and data scientists.
Key Takeaways
Use the tools and languages that are best suited to the job – Complete flexibility to problem-solving with novelty and creativity encouraged.
Be around very bright and lovely people.
Your intellectual curiosity and hard work contributions will be welcome to our culture of knowledge sharing, transparency, and shared fun and achievement.
Provide education and documentation to empower team members to make the most of technical resources.
Contribute to our software engineering culture of writing correct, maintainable, elegant, and testable code.
Utilize AWS services and tools such as S3, EventBridge, Athena, and DynamoDB to build a robust and scalable data architecture for data ingestion, processing, and storage.
Collaborate on data infrastructure that supports LLM-driven workflows – leveraging tools like Cursor to accelerate code development, enhance reproducibility, and streamline iteration on intelligent systems.