The Software Engineer III will design and develop cloud-native applications on AWS, focusing on event-driven architecture, API development, database management, and data engineering with Databricks. Responsibilities include implementing best practices in DevOps and collaborating with teams on application lifecycle management.
Job Description
The Planning and Analysis - Data Platform Team (FPNAE) is at the forefront of managing and optimizing finance-related data. We focus on effective data lake utilization, data governance, and seamless data integration through advanced ETL processes. Our goal is to deliver high-quality, timely data in a controlled manner, reducing risk and cost. We are looking for a Senior Application Engineer skilled in AWS, event-promoten architecture, RESTful API design, and modern application development, with expertise in Python frameworks, database management, and Databricks for data engineering.
Key Responsibilities
Required qualifications, capabilities and skills
The Planning and Analysis - Data Platform Team (FPNAE) is at the forefront of managing and optimizing finance-related data. We focus on effective data lake utilization, data governance, and seamless data integration through advanced ETL processes. Our goal is to deliver high-quality, timely data in a controlled manner, reducing risk and cost. We are looking for a Senior Application Engineer skilled in AWS, event-promoten architecture, RESTful API design, and modern application development, with expertise in Python frameworks, database management, and Databricks for data engineering.
Key Responsibilities
- Design and Develop Cloud-Native Applications Architect, build, and maintain scalable applications on AWS using event-driven patterns (e.g., Lambda, SNS/SQS, EventBridge).
- API Development Create robust RESTful APIs using Python frameworks such as FastAPI and Django, ensuring high performance and security.
- Database Engineering Design, implement, and optimize operational databases, primarily PostgreSQL, including schema design, indexing, and query optimization.
- Data Engineering & Analytics Collaborate with data teams to integrate applications with Databricks, supporting ETL pipelines, data processing, and analytics workflows.
- Application Lifecycle Management Participate in the full software development lifecycle, including requirements gathering, design, coding, testing, deployment, and maintenance.
- DevOps & Automation:
Implement CI/CD pipelines, automate deployments, and monitor application health using AWS-native and third-party tools. - Collaboration & Documentation:
Work closely with cross-functional teams (product, data, infrastructure) and document technical solutions, architecture, and best practices.
Required qualifications, capabilities and skills
- AWS Expertise Proven experience with AWS services (EC2, Lambda, S3, RDS, SNS/SQS, EventBridge, IAM, CloudFormation).
- Event-Driven Architecture Strong understanding and practical experience designing event-driven systems and microservices.
- RESTful API Development Deep knowledge of REST principles and hands-on experience building APIs with FastAPI and Django.
- Python Programming Advanced proficiency in Python, with experience in application engineering and scripting.
- Database Management Solid experience with PostgreSQL, including performance tuning and operational management.
- Databricks Knowledge Good understanding of Databricks platform, Spark, and data engineering concepts.
- DevOps Practices Experience with CI/CD, infrastructure as code, and application monitoring.
- Soft Skills Excellent problem-solving, communication, and teamwork abilities.
Top Skills
AWS
Ci/Cd
Databricks
Django
Event-Driven Architecture
Fastapi
Postgres
Python
Spark
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