Senior Data Engineer, Exposure

Responsibilities

• Build cloud-native data ingest and aggregation processes handling gigabytes of data per day
• Develop and optimize high-performance Spark jobs in Python to detect market manipulation and fraud
• Build and improve batch-based applications and real-time streaming pipelines processing billions of records
• Architect and maintain scalable data lakehouse environments using Parquet, Iceberg, and Delta Lake
• Collaborate on building scalable AWS API services that interface with the data layer
• Modernize the data stack toward highly automated, serverless architectures to support 10x capacity
• Debug production data quality issues and performance bottlenecks across distributed systems

Requirements

• Experience designing and implementing cloud-native, distributed data processing systems (AWS preferred)
• Deep expertise in Python and Apache Spark, including performance tuning and distributed computing
• Extensive experience working on backend systems and large-scale data architecture
• Proven ability to turn raw data into actionable insights through iterative development
• Interest in the cryptocurrency technology ecosystem and its unique data challenges

Preferred Qualifications

• Experience mentoring other engineers and leading cross-team data initiatives
• Proficiency with Terraform and Kubernetes (EKS) for orchestrating data workloads
• Familiarity with the "Modern Data Stack" and scaling large-scale data systems

About the Company

Chainalysis is the leader in blockchain investigation and compliance software. We provide complete knowledge of what is happening on blockchains through our data, services, and solutions, helping organizations navigate the ecosystem safely and with confidence.