Cloud DevOps Engineer - Data Quality, Vice President Cloud DevOps Engineer - Data Quality, Vice  …

J.P.Morgan
in Singapore
Permanent, Full time
Be the first to apply
Competitive
J.P.Morgan
in Singapore
Permanent, Full time
Be the first to apply
Competitive
Cloud DevOps Engineer - Data Quality, Vice President
In this role, you will be part of a global team responsible for building and managing data quality & governance solutions for managing the quality, integrity 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:
  • Develop, deploy & manage strategic data quality and governance 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 the business stakeholders & operations partners, collect requirements, identify gaps and drive demand prioritization and change management.
  • 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:
  • Bachelors Degree in Computer Science or Technology-related major
  • Minimum 10 years of experience with proven track record in business intelligence, analytics, big data implementation/ machine learning (ML) projects.
  • Hands-on experience in developing and deploying highly available and scalable Docker-based applications on Kubernetes platforms.
  • Proficiency in SQL, UNIX scripting and either Java or Python programming language.
  • Familiarity with various data processing paradigms (batch/streams etc.) and related tools (such as ETL tools/ Kafka / Apache Spark etc.)
  • Good to have experience in AWS services such as EC2, S3, EMR, MKS, Glue etc.
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