Senior Data Engineer | Location: Boca Raton, FL
Senior Data Engineer #1704
Position Summary:
We are seeking a Senior Data Engineer with a strong background in Python, data warehouses (BigQuery), and visualization tools to join a growing team of innovative and analytical engineers at a publicly-traded Fintech company in South Florida. In this role, you will utilize your subject matter expertise to drive transformational data and analytics initiatives that improve the effectiveness and efficiency of business functions for the enterprise. You will work closely with C-Level executives and different departments across the company making this a highly visible and influential position.
Experience and Education:
- Bachelor’s degree in Computer Science or equivalent experience
- 5+ years of experience in Data Engineering
- 3+ years of Python development experience
- Experienced in Business Intelligence, ETL, Data Warehousing, and Data Visualization tools
Technology Skills and Strengths:
- Python
- BigQuery
- ETL
- XML/JSON
- API calls
- AWS
- GCP
- Cloud Storage
- Cloud Run
- GKE
- Data Studio or similar visualization tools
- SQL
- MySQL / MongoDB
- Data Warehousing
- Data Integrations
- Microservices
- ERP experience, a plus
Primary Job Responsibilities:
- Create and write reusable, testable, and efficient Python code and integrate multiple data sources and databases.
- Determine best practices, guidelines, and standards for the configuration of application deployment containers and databases.
- Assist with building data warehouses.
- Create reusable patterns, frameworks, and components.
- Provide scalable solutions.
- Develop an end-to-end Python-based pipeline to capture key data elements from the systems and automate verification of algorithm findings.
- Uses documented procedures to create a source-to-target mapping, document code map capturing business and technical metadata, and complete data lineage.
- Manipulate and analyze high-volume, high-dimensionality data from various sources using a variety of tools and data analysis techniques.
- Evaluate emerging technologies, open-source libraries and provide recommendations.
- Perform profiling of data captured by the pipeline, document results, and present findings.
- Support and maintain existing data software products, applications, and interfaces
