VP, Big Data Engineer, Big Data Analytics Group, Data Management Office
- Permanent, Full time
- United Overseas Bank
- 14 Dec 17
VP, Big Data Engineer, Big Data Analytics Group, Data Management OfficeThe Data Management Office (DMO) is a business function that covers Enterprise Data Governance, Data Management, Big Data Analytics and Enterprise Data Strategy. Data Management Office ensures that UOB meets all data governance standards set by data regulators and optimize data management and usage to help UOB make smarter, faster and more accurate decisions and to improve operational efficiency.
The Big Data Analytics Group (BDAG) leads the transformational build, use, and deployment of the banks next generation analytics capabilities across the organization. This exciting role will play a pivotal part as an Analytics Centre of Excellence that will take analytics to the next level through use of latest data and analytics technology currently being deployed. You will work either individually or in project teams as a subject matter expert to deliver new Big Data and Machine Learning solutions for our business partners.
Your main responsibilities include:
- Develop and deploy real-time, scalable and optimized Data Analytics Pipelines to empower data transformation, insight discovery and predictive modeling on complex datasets.
- Partner with data scientists and business intelligence developers in assembling capabilities and implementing solutions to address the analytics needs of the group.
- Apply Software Engineering best practices in every phases of the Software Development Life Cycle, such as requirement analysis, algorithm design, code review, code optimization, functional testing, implementation, maintenance and documentation.
- Support the Enterprise Data Architecture and Governance Program by applying Data Engineering Capabilities to design, build, and scale our data assets in accordance with our business priorities
- Drive Innovation initiatives under CDO guidance and directives.
- Min Degree in Data, Software Engineering, or Computer Science or a related field
- Min 5 years data analytics/data engineering working experience in banking / financial services industry
- Possess a selection of skills and experience with
o Big data technologies (e.g. Hadoop, Spark, Impala, Hive, Pig, Sqoop, Kafka, etc.)
o Enterprise database and data warehouse technologies (e.g. SQL on Teradata, Oracle, etc.)
o Data extraction, loading and transformation technologies and tools
o Data wrangling tools
o Analytics tools and languages (e.g. R, SAS, Python, Java, Scala, etc.)
- Deep understanding in Computer Science fundamentals such as algorithm design and complexity analysis
- Demonstrated track records of success in data engineering or software development capabilities
- Experience working in an agile environment using agile tools and practices
- Strong communication skill, and capable of working individually and as a team