Role Overview
As an Application Development and Support Engineer, you will be responsible for developing, maintaining, and supporting data-driven applications, ETL workflows, and web services that underpin investment risk and research platforms.
You will work closely with on-site teams in an Agile environment to deliver reliable, scalable, and high-quality technical solutions.
While domain knowledge in investment risk is a plus, the primary focus is on strong technical skills, automation, and best practices in data engineering, application support, and web service development.
Key Responsibilities
- Develop, maintain, and support Python-based applications, automation scripts, and Flask web services to enable data access and integration.
- Design, implement, and optimize SQL queries and database objects to enable efficient data access and transformation.
- Build, manage, and monitor ETL pipelines using tools such as dbt, Airflow, and Azure Data Factory, ensuring data quality and operational reliability.
- Develop RESTful APIs and microservices using Flask to support internal and external data consumption and integration needs.
- Troubleshoot and resolve application, web service, and data pipeline issues promptly to minimize downtime and maintain platform stability.
- Collaborate with cross-functional teams including quant engineers, data engineers, analysts, and architects to understand requirements and deliver solutions.
- Implement CI/CD pipelines and automation to streamline deployment and testing of data workflows, applications, and web services.
- Document technical solutions, processes, and support procedures clearly to facilitate knowledge sharing and operational continuity.
- Continuously improve processes, automation, and monitoring to enhance efficiency and platform robustness.
Technical Skills
- Proficient in Python programming with experience in scripting, automation, and working with data libraries (e.g., Pandas).
- Experience developing RESTful web services and APIs using Flask or similar Python web frameworks.
- Strong SQL skills for querying and manipulating relational databases and data warehouses (Snowflake, Azure Synapse, or similar).
- Hands-on experience with ETL and orchestration tools such as dbt, Airflow, and Azure Data Factory.
- Familiarity with CI/CD practices and tools for Python applications, data workflows, and web services.
- Experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Understanding of Agile software development methodologies and ability to work effectively in Agile teams.
- Basic knowledge of cloud platforms, preferably Azure, including familiarity with cloud data services.
- Good problem-solving skills and a proactive approach to identifying and resolving technical issues.
Professional Skills
- Strong sense of ownership and accountability for assigned work.
- Effective communication skills to articulate technical issues and collaborate with diverse teams.
- Ability to work independently and as part of a collaborative Agile team.
- Attention to detail and commitment to delivering high-quality solutions on time.
Preferred (Not Required)
- Prior exposure to investment risk and research domains or financial services environments.
- Experience integrating or supporting financial systems such as Aladdin, Clearwater, FactSet, or PledgePath.
- Familiarity with monitoring, alerting, and incident management tools.
- Understanding of data governance, compliance, and security best practices relevant to financial data
(ref:hirist.tech)
