Senior Software Engineer (Java, SQL and AWS)
The Senior Software Engineer role focuses on the design and implementation of in-house software solutions, or the integration of third-party products (including software-as-a-service) used by our business teams. A successful candidate will be involved in the entire development cycle, starting with the support of the business analysis phase up to production deployment and third-level support.
Responsibilities:
- Designs and implements solutions that are high-performing, secure, and cost-efficient.
- Prepares and validates technical specifications for junior colleagues and external developers.
- Understands the business aspects of the platform and assists in defining project scope and objectives, engaging all relevant stakeholders and ensuring technical feasibility.
- Delivers projects on time, within scope, and within budget.
- Possesses extensive experience in designing, programming, and implementing large-scale software solutions while collaborating with multiple stakeholders.
- Creates and maintains comprehensive technical documentation.
- Plans time diligently, prioritizes tasks effectively, and communicates progress transparently with the project team.
- Manages relationships with internal clients and peers.
- Proposes strategic approaches to advance the business applications platform within Partners Group.
Minimum Skills/ Experience Required:
- Excellent record of academic achievement, ideally holding a bachelor's or master's degree in computer science or another scientific or quantitative discipline.
- 8-10 years of experience in software engineering, preferably within the financial industry.
- Advanced knowledge of Java.
- Hands-on knowledge of AWS services and cloud infrastructure
- Experience coordinating with business users and developers to solve business problems, with an entrepreneurial mindset focused on continuous improvement
- Confirmed hands-on experience with relational databases and SQL.
- Practical experience with cloud computing.
Good to have:
- Application and data integration strategies, such as AWS Glue, Apache Airflow and Control-M
- Serverless computing architectures
- Microservices architecture and RESTful services
- CI/CD pipelines and DevOps practices
- Messaging and data streaming technologies, such as Kafka or Amazon Kinesis
- AI-powered coding tools like Cursor, GitHub Copilot and Amazon Q
- Snowflake for data warehousing solutions
- Using pre-trained AI models to enhance software functionality.
