Who are we?
FalconX is the most advanced digital asset platform for institutions. We provide trade execution, credit & treasury management, prime offering and market making services. Given our global operations, industry-leading technology and deep liquidity, we have facilitated client transactions of $1 trillion in volume. Our products & services are regulated, compliant and trusted.
We are a team of engineers, product builders, institutional sales and trading leaders, operations experts, and business strategists. Our teammates have entrepreneurial experience and come from companies such as Google, Apple, Paypal, Citadel, Bridgewater, and Goldman Sachs. And, we embody our values: Think big; Drive bold outcomes; Be one team; Iterate with speed; and be an entrepreneur.
We prioritize learning. Outcomes are mission-critical, but we also believe that learning in success and in failure will drive our continued success. Our industry is emergent - there’s no shortage of experiments to get involved with and to continue growing and learning together.
Impact
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.
What you’ll be working on:
- 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.
Skills you'll need:
- 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
Nice to haves:
- Experience with AWS, and especially RDS, MSK, EMR, S3, Glue, Kinesis etc
- Prior experience with Databricks, Snowflake, Airflow and Delta Lake
Base pay for this role is expected to be between $155,000 and $245,000 USD. This expected base pay range is based on information at the time this post was generated. This role will also be eligible for other forms of compensation such as a performance linked bonus, equity, and a competitive benefits package. Actual compensation for a successful candidate will be determined based on a number of factors such as skillset, experience, and qualifications.
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