Data Analyst - Banking Data Governance

Job Description Summary:

Data Management - Data Quality is responsible for multiple aspects of data management and operations for the firm, including database administration and design, business intelligence and data architecture, data analytics, governance, and quality. Specializes in supporting improvement and performance activities by providing measurement, evaluation, and assessment services relating to data quality and data production. Provides solutions and advice in process evaluations, performance monitoring, and statistics, managing and executing data processing.

Your main responsibilities include:

Gathering and documenting business requirements & functional specifications on data related initiatives.

Perform data investigation and data analysis to support Bank wide user’s queries on EDAG.

Perform data profiling and gap analysis, source to target mappings, data issue capturing, resolution and escalation.

Provide end-to-end project delivery support, including requirements walkthrough, user acceptance testing, defect support, continuous validation and assisting with rollout activities.

Able to construct medium to complex SQL queries for data quality checks, reconciliation and exception investigation.

Provide support to Bank wide users’ requests.

Build and manage dashboards for monitoring and analytical purposes.

Documentation and Administrative support – coordination and assistance in the project implementation, system and process documentation, minutes taking etc.

Foster strong working / collaborative relationships with the business & technology stakeholders.

Requirements:

Degree in Business Computing or Computer Science or related disciplines.

At least 1 to 3 years of relevant working experience.

Strong knowledge of SQL and Python.

Familiar with banking products.

Proficient in MS Excel, MS Word and MS PowerPoint.

Possess good analytical skills and problem-solving skills.

Soft skills, able to work independently with users on requirements gathering or issues investigation.

Strong communication and interpersonal skills.

Familiar with general data architecture concept, including data warehouse and big data technology is preferred.

Knowledge on Hadoop and Discovery tools (e.g., Qliksense, HUE).

Familiar with AI technology and have experience working on some AI tools.