At GXS Bank, we are a digital bank on a mission to make banking better for Singapore&aposs everyday consumers and small businesses. We pride ourselves on our dynamic culture and our commitment to fostering growth and innovation.
Validus Capital Singapore, now part of the GXS Bank family, is the leading SME financing platform in Singapore. Validus Capital has received numerous accolades, including 1st place at the MAS Fintech Awards, 1st runner-up at the SFF Fintech Awards, and recognition as one of LinkedIns Top 15 Startups in Singapore, as well as several other industry awards.
This role sits within GXS Capital (Validus Capital Pte Ltd) - now a valued part of the GXS Bank family - where were building the future together, backed by the strength, resources, and culture of GXS Bank.
We are looking for a talented and experienced Data Engineer to join our team and play a crucial role in managing and automating our data pipeline to support our growth. The role will report to the Head, Data, Models and Portfolio Management
Key Responsibilities:
- Design, develop, and maintain scalable and robust data pipelines and ETL processes to ingest, parse, process, and store structured and unstructured data from various sources
- Implement change data capture (CDC) capable of capturing changes made to source data and propagating them downstream to other systems or applications.
- Develop and maintain data architecture and data models to support efficient querying and reporting, using data platforms such as Snowflake and AWS Redshift, MySQL, MongoDB, S3.
- Utilize dbt (Data Build Tool) for transforming and modeling data in the warehouse.
- Collaborate with data scientists, and business stakeholders such as product, sales, risk and operations to understand their data requirements and ensure data integrity, accuracy, and timeliness.
- Collaborate with the technology team regarding data architecture and source databases
- Collaborate with the data scientists to develop and maintain BI dashboards and visualizations using tools like Power BI and Tableau to provide actionable insights for business decision-makers.
- Monitor and troubleshoot data pipeline performance, ensuring optimal data flow and minimal downtime.
- Implement Data Observability and Data Quality practices using the relevant tools and set up data alerts/reporting of Data Observability and Quality metrics
- Support ad hoc data extraction, processing and analysis with scripting while working towards automation in the future
- Implement data security best practices to ensure data privacy and compliance with relevant regulations.
- Continuously research and adopt new technologies, tools, and best practices to improve data engineering processes and infrastructure.
Requirements:
- Bachelor&aposs degree in Computer Science, Information Technology, Engineering, or a related field.
- 3-5 years of experience in data engineering or a related field, with a strong background in data architecture and data modelling
- Background in software engineering and experience with CI/CD, DevOps, K8s is a strong plus.
- Proficient in SQL, Python, and/or other programming languages relevant to data engineering.
- Experience with data ingestion, processing, and storage tools and technologies, such as Snowflake, Redshift, MySQL, MongoDB, S3, Appflow/Fivetran/DMS, Airflow/Dagster, Kafka, dbt, AWS Glue.
- Strong understanding of data warehousing concepts, ETL processes, and data modeling best practices.
- Experience using one or more cloud data services especially AWS
- Experience with Optical Character Recognition (OCR) for data extraction is a strong plus.
- Familiarity with BI tools and platforms, such as Power BI, Tableau, or Looker.
- Familiarity with one of the data cataloguing tools such as Alation, Collibra is a plus.
- Ability to work independently and collaboratively in a fast-paced, dynamic/somewhat unstructured environment.
- Strong emphasis towards delivering business outcomes and collaborating with business stakeholders to ensure the data solutions are fit for the business use cases at hand.
