About the Role :

A "Senior Data Engineer" is mid-level professional leading the design, build and evolution of the inhouse data platforms. You lead the construction of datasets requested by various stakeholders, the build and maintenance of the resulting data pipelines. You closely work in collaboration with our data analysts, data scientist and business application development teams in delivering data solutions. Our hybrid work model is designed to give you the best of both worlds-flexibility and face-to-face collaboration. Employees are required to be present in the office on Mondays, Wednesdays and Fridays each week. This means

you'll be in the office at least three days a week, with the option to work remotely on the other days, based on manager approval and business needs. This approach helps us stay connected as a team while giving you the flexibility to work in a way that suits you.

Design :

1. Analyse relevant internally and externally sourced data (raw data) to generate BI and Advanced Analytics datasets based on your stakeholders' requirements.

2. Design data pipelines to curate sourced data into the inhouse data warehouse.

3. Design data marts to facilitate dataset consumption out of the inhouse data warehouse by business and IT internal stakeholders.

4. Design data model changes that align with the inhouse data warehouse standards.

5. Define migration execution activities to move data from existing database solutions to the inhouse datawarehouse.

Engineer :

1. Regular housekeeping of raw data and data stored in the inhouse data warehouse.

2. Build and maintenance of data pipelines and data platforms.

3. Build data solution prototypes.

4. Explore ways to enhance data quality and reliability.

5. Identify and realize opportunities to acquire better data (raw data).

6. Develop analytical tooling to better support BI and Advanced Data Analytics activities.

7. Execute data migration from existing databases to the inhouse data warehouse.

8. Promote and champion data engineering standards and best-in-class methodology.

You will have the following qualifications :

1. Bachelor's or master's degree in Computer Science, Information Technology, Engineering or related quantitative discipline from a top tier university.

2. Certified in AWS Data Engineer Specialty or AWS Solution Architect Associate

3. Snowflake SnowPro Core Certification.

4. 7+ years of experience in data engineering or relevant working experience in a similar role, preferably in the financial industry.

5. Strong understanding or practical experience of at least one common Enterprise Agile Framework e.g. Kanban, SAFe, SCRUM, etc.

6. Strong understanding of ETL, data warehouse and BI(Qlik) and Advanced Data Analytics concepts.

7. Deep knowledge of cloud-enabled technologies - AWS RDS and AWS Fargate, etc.

8. Experience with databases and data warehouses - Snowflake, PostgreSQL, MS SQL.

9. Strong programming skills with advanced knowledge of Java and/or Python.

10. Practical experience with ETL tools such as AWS Glue, etc.

11. Strong critical-thinking, analytical and problem-solving skills.

12. Excellent communicator with team-oriented approach.