Apex Fintech Solutions (AFS) is looking to solve the problem of processing and analyzing large volumes of financial data to support strategic decision-making in the fintech and wealth tech community. The goal is to build scalable cloud infrastructure that powers analytics capabilities and supports clearing and custody services for clients such as Stash, Betterment, SoFi, and Webull.
Requirements
- Expert-level knowledge of Google Cloud Platform (GCP); GCP Data Engineer certification strongly preferred
- Expert proficiency in SQL and Python; familiarity with Java is a plus
- Experience with ETL/ELT tools and frameworks (Apache Airflow, AWS Glue, dbt, GCP Dataflow)
- Strong experience with relational database systems (PostgreSQL, SQL Server) and cloud data warehouses such as Bigquery, Snowflake
- Experience with CI/CD systems, Infrastructure as Code (Terraform), and Kubernetes
- Experience with change data capture (CDC) tools like HVR, Datastream, Dataflow, Kinesis
- Proficiency with Git and modern CI/CD development practices
Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines for our enterprise data warehouse and data lake
- Implement robust data processing systems that support our Data Products
- Build systems to handle real-time and batch data updates using change data capture (CDC) tools such as HVR, Dataflow, Datastream
- Build and extend existing systems that process, store, and move streaming and batch data from SQL-based sources to centralized GCP storage and/or cloud data warehousing platforms
- Build complex views that enable convenient and intuitive access to datasets
- Implement comprehensive data quality checks and monitoring to ensure accuracy and reliability
- Optimize existing data workflows for improved performance, cost efficiency, and scalability
Other
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field
- 5+ years of experience in data engineering, cloud data engineering, or similar roles
- Experience in financial services strongly preferred
- This role operates in a hybrid capacity, requiring on-site collaboration three days per week
- Strong understanding of data warehousing concepts and dimensional modeling
