Senior Software Engineer, Circle

• 4+ years of experience in software engineering, preferably focused on data systems
• Familiarity with building or maintaining scalable data infrastructure for batch, micro-batch, or streaming pipelines
• Exposure to business domains such as payments, banking, or blockchains is a plus
• Understanding of data governance concepts like data lineage, quality, and access control
• Interest in open-source data tools and technologies
• Comfortable working through technical problems, even when requirements are not fully defined
• Proactive, curious, and eager to learn and contribute in a fast-paced environment
• Good communication skills and ability to collaborate with team members across functions and locations

Desirable

• As a member of the Data Platform Engineering team, you will own and evolve the core Data/ML platform — including data ingestion and processing (with a focus on both traditional and blockchain data sources), ETL/ELT pipelines, data governance and security compliance, analytics and visualization tooling, data modeling, and warehousing
• You will also design and build systems to monitor data pipelines and on-chain activity to ensure reliability, performance, and observability
• This role requires close collaboration with Infrastructure, Data Science, and Engineering teams to align on diverse requirements and deliver scalable, high-impact solutions
• You will also participate in maintaining existing infrastructure and join the on-call rotation to ensure the liveness and stability of services
• These components power our Product, Engineering, Analytics, and Data Science functions by enabling experimentation, operational excellence, and actionable insights that drive business growth
• Design, build, and operate data platform services such as warehousing, orchestration, data catalogs, and ingestion frameworks
• Develop and maintain scalable ingestion pipelines, including onchain/blockchain data ingestion, with robust handling of node APIs, rate limiting, and data consistency
• Implement data alerting mechanisms to monitor critical events or anomalies in ingested data (e.g., specific on-chain transactions, contract changes, or volume spikes)
• Handle ingestion pipelines that operate across a broad range of scales, from small partner datasets to high-throughput blockchain transaction streams
• Continuously improve platform operations through better monitoring, performance tuning, reliability enhancements, and resource optimization
• Collaborate across Product, Engineering, Data Science, Security, and Compliance teams to establish data contracts, governance, and lifecycle management
• Serve as a domain expert in data warehousing, data modeling, pipeline orchestration, and ensuring data quality at scale
• Provide ML/AI platform capabilities for data scientists to run experiments, manage training data, and perform feature engineering
• Build and maintain foundational services such as
• Data asset cataloging and lineage tracking
• Data versioning and quality metrics
• Auto-backfilling for incomplete data scenarios
• Fine-grained access control on datasets