Job responsibilities

• Implement PoC and pilot projects  for new platform features and technologies under the guidance of senior architects.
• Contribute to architecture documentation , including class diagrams, data architecture, functional architecture, and application architecture.
• Support the design and development of microservices  for automated investment workflows.
• Assist in optimizing data pipelines  for portfolio management and tax-smart investing, including Airflow DAG implementation.
• Participate in the development of machine learning platforms  for quantitative analytics, integrating with portfolio management solutions.
• Help maintain data warehouse and data lake solutions  for analytics and reporting (Redshift, Snowflake, etc.).
• Support observability solutions  (monitoring, logging, tracing, alerting) to ensure system health and performance.
• Contribute to the implementation of non-functional requirements (NFRs)  for performance, scalability, reliability, and security.

• Collaborate with product, engineering, and data teams  to deliver robust, scalable solutions.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience

• Proficiency in Python and database technologies like AWS Aurora (SQL, NoSQL).
• Experience in data modeling and database design for both transactional and analytical workloads. 
• Database tuning for optimal platform performance to meet Non-functional requirements
• Experience with public cloud (AWS) services (EC2, S3, Lambda, RDS, ECS, etc.).
• Familiarity with distributed messaging systems (Kafka, RabbitMQ).

• Experience with Redis for caching and real-time data processing.

Preferred qualifications, capabilities, and skills

• Experience in financial services, asset management, or fintech.

• Knowledge of tax-smart investing concepts and portfolio management.

• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)