Ava Labs is hiring a

Data Engineer, Blockchain Data

The Data Platform team is responsible for providing simplified Data and API services to the overall Avalanche Ecosystem. We are seeking an experience Data Engineer with experience working with high-throughput systems. This particular role will be expected to assist with a variety of data related products and help identify real world insights from on-chain data. Previously API experience is a notable plus.

WHAT YOU WILL DO

• Design and build robust, scalable & reliable real-time pipelines to ingest various types of blockchain data into cloud-native databases
• Improve Ava Labs’ products and decision-making by growing and optimizing our current data sets
• Identify data needed for various business and engineering projects, collaborate with other engineers to create scalable solutions for ingesting and processing the required data
• Work with the team and maintain best practices for managing and accessing cloud-native databases and data warehouses
• Collaborate closely with backend engineers to support new and existing APIs. Build features for theAvalanche Explorer, Core Wallets (Core Ext,Web Wallet), and other data-intensive applications
• Partner with product teams to develop systems to gain real-world insights from on-chain data

WHAT YOU WILL BRING

• BS in Computer Science or equivalent experience
• 2-3+ years of hands-on data engineering experience
• 2+ years of building cloud-native, high-throughput data processing systems
• 2+ years working with SQL/NoSQL databases
• Familiar with the concepts of containerization and its management i.e. Docker and Kubernetes
• General understanding of blockchain data structures (EVM, UTXO, etc) is required
• Experience working in Spark and Golang is preferred
• Experience working with Kafka or similar data streaming services is preferred
• Experience working on Rest APIs and Node.js is a plus

Salary Range: $123,200 to $154,000

(**This is not a guarantee of compensation or salary, a final offer amount may vary based on factors including but not limited to experience and geographic location.)

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