Senior Data Software Engineer, FalconX

• Degree in Computer Science, a related field or equivalent professional experience
• 3+ years of strong experience with data transformation & ETL on large data sets using open technologies like Spark, SQL and Python
• 3+ years of complex SQL with strong knowledge of SQL optimization and understanding of logical & physical execution plans
• You have at least 1 year working in AWS environment, and should be familiar with modern web technologies like AWS cloud, MySQL database, Redis caching, messaging tools like Kafka/SQS etc
• Experience in advanced Data Lake, Data Warehouse concepts & Data Modeling experience (i.e. Relational, Dimensional, internet-scale logs)
• Knowledge of Python, Spark (Batch/Streaming), SparkSQL and PySpark
• Proficient in at least one of the following Object-oriented programming languages -- Python / Java / C++
• Effective craftsmanship in building, testing, and optimizing ETL/feature/metric pipelines
• Experience with Business Requirements definition and management, structured analysis, process design, use case documentation
• A data-oriented mindset

Desirable

• FalconX’s Data Infra team builds and operates systems to centralize internal and third-party data, make it easy for engineering, data science, business intelligence, accounting, compliance teams to transform and access that data for analytics and machine learning, and power end-user experiences.
• As a Data Engineer on the team, you will contribute to the scalable Batch and Streaming ETL pipelines , DWH design and Data modeling, Data Governance initiatives tools and applications that make that data available to other teams and systems
• Provide technical and thought leadership for Data Engineering and Business Intelligence
• Create, implement and operate the strategy for robust and scalable data pipelines for business intelligence and machine learning
• Develop and maintain core data framework and key infrastructures
• Data Warehouse design and data modeling for efficient and cost effective reporting
• Define and implement Data Governance processes related to data discovery, lineage, access control and quality assurance