J.P.Morgan - Singapore

Job Description:
In this role, you will be part of a global team responsible for building and maintaining predictive data quality solutions for managing the quality, integrity and validity of the firm's data by applying statistical approaches and machine learning techniques.
You will work with varied stakeholders across businesses, architecture and technology and implement innovative DQ solutions using both vendor applications and internal tools.
In line with the overall Data Architecture goals of Engineering & Architecture (E&A) group within CIB, you will be responsible to deliver the technical book of work in timely manner while fulfilling efficiency, quality and optimization targets.
Key Responsibilities:

  • Code, test, deploy & support strategic data quality framework using off-the-shelf third party applications and internal tools.

  • Ensure timely delivery of technical solutions in line with E&A's overall data architecture goals and visions.

  • Understand and manage operational processes, work closely with business stakeholders & operations partners, collect requirements, identify gaps and develop innovative technical solutions.

  • Participate in various phases of solution design, solution development, UAT support, stakeholder communication and production deployment processes.

  • Be a data storyteller, deliver data insights in compelling manner and articulate findings clearly and concisely via presentations, discussions and visualizations.

This role requires a wide variety of strengths and capabilities, including:

  • Bachelor Degree, Technology or Engineering major preferred

  • Minimum 4 years of experience with proven track record in any data quality, data governance, business intelligence, analytics or big data implementation projects.

  • Must have hands-on experience in at least one of the following Data Quality or Analytics tools: Collibra OwlDQ / Informatica DQ/ Talend DQ, Tableau, QlikView or similar.

  • Experience in Hadoop ecosystem (Cloudera/Horton) and Apache Spark

  • Proficiency in writing SQL and strong conceptual knowledge in relational and NoSQL databases.

  • Good to have experience in AWS services such as EC2, S3, EMR, MKS, Glue etc.

  • Good analytical skills