My client is a Singaporean investment firm. They are looking for a Data Engineer to join the team to build and develop the firm's data foundation and infrastructure. You will help ingest, analyse, and combine data with context across all industries and asset classes to enable investment decisions and enhance investment process.
Responsibility
- Play a pivotal role in building and supporting enterprise investment data & analytics systems consumed by investment professionals and platforms across the firm. You will also develop and maintain relationships with business leaders, product management and technical teams to understand priorities and expected business outcomes.
- Develop business solutions using your strong analytical skills, and help the team bring technology value directly to the business. You will also be exposed to key investment processes across the firm, learning valuable business domain knowledge.
- Lead software delivery for fast-moving agile projects with modern DevSecOps practices (e.g. Github, Jfrog, Jira) and data technologies (eg. Databricks, Python, DBT, Airflow). You will also work with external experts and solution architects on with AWS cloud native technologies.
- Actively provide technical leadership, direction and mentorship to raise the quality bar for engineering talent – attracting, retaining, and improving the best developers in the industry.
- Become an excellent team player with a collaborative mind-set, you will work directly with investment and technology professionals at different levels. You will also work alongside experienced professionals across our extended Technology team as well as have exchanges with other industry partners.
What they are looking for
- 8+ years hands on experience working and leading development work in data engineering, including data analytics, data transformation, data modelling, reporting, data visualization, preferably in financial institutions or in asset management services
- Experience in the following skills:
- Extensive experience in Python, PySpark, SparkSQL, SQL, DBT, and Pandas
- Good understanding and experience with cloud services, such as AWS
- Good experience with Docker, Kubernetes, GitHub workflows, and other DevOps capabilities such as CI/CD pipelines and Terraform
- Good experience in visualization or BI tools such as Tableau, or Microsoft Power BI
- Strong understanding in data architecture, management & governance concepts related to lake-house, data lineage and data quality
- Willingness to learn with attention to detail, demonstrating a strong passion in technology and/or financial data
- Strategic thinker and problem solver who approaches tasks with motivation and commitment
- Good system design thinking being able to structurally breakdown problems, simplifying complex problems into parts to drive overall business outcomes
- Good presentation skills, and communication skills across technical and non-technical audiences, effectively translating complex technical concepts into business terms
- Strong people leadership to engage with Data Engineers and guide hands-on development to demonstrate their mentorship and connectedness with the everyday needs of developers
- Strong business leadership to engage with our stakeholders in all functions and levels. Ability to collaborate and influence cross-department business and technical partners to contribute to the development of technical strategies
- Bachelor's or equivalent degree in Science, Technology, Engineering and Mathematics (STEM) related discipline is advantageous.
