Full-Time Associate Solutions Architect

Associate Solution Architect will provide technical leadership, architecture, governance, and oversight of CFRA's next generation of data science and data processing software using a modern cloud-native technology stack with Python on AWS cloud infrastructure.

This is a rare opportunity to make a big impact on both the team and the organization by being part of the design and development of application frameworks that will serve as the foundation for all future development at CFRA.

The ideal candidate has a passion for solving business problems with technology and can effectively communicate business and technical needs to stakeholders.

Key Responsibilities

1. Requirement Analysis: Collaborate with stakeholders to understand business requirements and data sources and define the architecture and design of data engineering models to meet these requirements.
2. Architecture Design: Design scalable, reliable, and efficient data engineering models, including algorithms, data pipelines, and data processing systems, to support business requirements and quantitative analysis.
3. Technology Selection: Evaluate using Proof of Concepts (POCs) and recommend appropriate technologies, frameworks, and tools for building and managing data engineering models.
4. Data Processing: Develop and implement data processing logic, including data cleansing, transformation, and aggregation, using technologies such as AWS Glue, Batch, Lambda.
5. Quantitative Analysis: Collaborate with data scientists and analysts to develop algorithms and models for quantitative analysis.
6. Model Evaluation: Evaluate the performance of data engineering models using metrics and validation techniques.
7. Data Visualization: Create visualizations of data and model outputs to communicate insights to stakeholders.
8. Monitoring and Logging: Implement monitoring and logging solutions for data engineering models.
9. Security and Compliance: Ensure data engineering model architecture complies with security best practices.
10. Documentation: Create and maintain documentation for data engineering model architecture, design, and implementation.
11. Collaboration: Collaborate with cross-functional teams.
12. Continuous Improvement: Stay updated with the latest trends, tools, and technologies in data engineering and quantitative analysis.

Desired Skills and Experience

• 10+ years of development experience on enterprise applications
• Understanding of data engineering principles and practices
• Proficiency in Python, R, Java, or Scala, and experience with SQL
• Familiarity with big data technologies
• Proficiency in using AWS cloud services
• Understanding of data integration techniques and tools
• Knowledge of database systems
• Excellent problem-solving skills
• Strong communication and collaboration skills
• Commitment to continuous learning
• Bachelor's Degree in Computer Science, Software Engineering, or related field (or equivalent experience)

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