• 8+ Years in Software Engineering
• Proficient in at least one primary programming language (e.g. Java, Scala, Python) and comfortable working with SQL
• Ability to write elegant code and comfortable with picking up new technologies independently
• Enjoy helping teams push the boundaries of analytical insights, creating new product features using data, and powering machine-learning models
• Have a strong background in developing distributed systems with experience in scalable data pipelines
• Familiar with big data technologies like Spark or Flink and comfortable in engineering data pipelines using big data technologies on financial datasets
• Experience with RESTful APIs and server-side APIs integration
• Highly or conceptually familiar with AWS cloud resources (S3, Lambda, API Gateway, Kinesis, Athena, etc.,)
• Experience with CI/CD pipeline orchestration, leveraging Gitlab and Terraform
• Experience with administration of Docker or Kubernetes infrastructure
• Appreciate the importance of excellent documentation and data debugging skills
• Excel at taking vague requirements and crystallizing them into scalable data solutions
• Excited about operating independently, demonstrating excellence, and learning new technologies and frameworks

Desirable

• This is a high impact role. You will build real-time data pipelines and a data lake for valuable internal tools used by leadership, compliance, finance, and product teams to make strategic business decisions
• You will be responsible for our Data API that powers public-facing applications used globally to follow the open-source ledger
• Build real time data pipelines and tools to keep pace with the growth of our data and its consumers
• Power our externally-facing data APIs and applications built on top of them
• Build foundational systems and services that allow users to focus on business and application logic via higher level programming models
• Design and implement systems for scalability, availability and graceful degradation
• Build frameworks for measuring and monitoring data quality and integrity
• Identify and analyze requirements and use cases from multiple internal teams (including Finance, Compliance, Analytics, Data Science, and Engineering); work with other technical leads to design solutions for the requirements