Vp, Data Engineer

**About UOB**: United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values - Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers. **About the Department**: The **Technology and Operations **function is comprised of five teams of specialists with distinct capabilities: business partnership, technology, operations, risk governance and planning support and services. We work closely together to harness the power of technology to support our physical and digital banking services and operations. This includes developing, centralising and standardising technology systems as well as banking operations in Singapore and overseas branches. **Responsibilities**: You will also be responsible for quality assurance of the team’s delivery in conformance with the Bank-defined software delivery methodology and tools. You will partner with other technology functions to help deliver required technology solutions. - Create frameworks, technical features which helps in faster operationalisation of Data models, Analytical models(including AI/ML) and user generated contents (dashboards, reports etc) - Effectively partner with citizen data scientists in enabling faster adoption of AL/ML model based systems - Independently install, customise and integrate software packages and programs - Carry out POCs involving new data technologies - Create technical documents such as solution design, program specifications for target solutions - Performance tuning - Work with production support team members to conduct root cause analysis of issues, review new and existing code and/or perform unit testing - Perform tasks as part of a cross functional development team using agile or other methodologies and utilising project management software **Job Requirements**: **Functional skillsets** TEAM < > Hands-on experience in implementing large scale data warehouse & analytics platforms in financial services industry with good functional knowledge of products & services offered in Retail bank / Wholesale / Global Markets covering some of the following analytics domains: - Data Modeling, Data mapping for Data Warehouse and Data Marts solutions - FSLM or similar industry models - Financial domain - Retail, Wholesale, Compliance, Digital - Experience in analytics - Finance Analytics, Credit Risk Analytics, Credit Scoring, Financial Crime Analytics - Experience in decision systems - Campaign Analytics, Credit Analytics- Expertise in design of role based fine grained access control - Designing cloud ready data solutions, Virtualization **Technical skillsets** - TEAM < >- Expertise in implementing Teradata based EDW and Data mart solution using ETL tool such as (Informatica Power Centre, BDM), GCFR based framework, BTEQ scripts - Expertise in implementing Hadoop based Data mart using Spark based framework (Java, Scala, Pyspark) - Good knowledge and working experience in data loading into Teradata using different load pattern (TPT, MLOAD, FAST Load), data compression (MVC, BLC) - Expertise in implementing Data Governance tools; Data Lineage (eg: Informatica MM, EDC), Business Glossary and Data Quality - Expertise in implementing Reference data management (Data standardization, Hierarchy maintenance) using tools (eg: MDM,RDM) - Good knowledge and working experience in Teradata FSLM or similar industry standard data model - Expertise in Cloudera CDH / CDP components - Good knowledge in developing Spark based ingestion framework (Java, Scala, Pyspark) - Experience in building and operationalising feature pipeline to support AI/ML model execution, data pipelines for supporting large scale data warehouse/data marts Additional requirements - 2 to 3 technical certifications from enclosed list: - Cloudera Hadoop distribution - Hive, Impala, Spark, Kudo, Kafka, Flume - Teradata - Bteq, Query Grid, GCFR, MDM, Data Mover, BAR - Informatica Data Integration - PC, IDR, BDM, MM, IDQ, EDC - Data modelling tools (Erwin) - QlikSense - Microsoft - R - Data science workbenches - Cloudera Workbench, Jupyter, DataRobot, H2O.AI, IBM DSX - Data Virtualization tool (Denodo, Dremio) - AS400 - Language - SQL, Java, Python, Scala, Pyspark - Automation / scripting - CtrlM, Shell Scripting, Groovy **Be a part of UOB Family**: