Banking Data Analyst - SQL & Data Quality Insights

HELIUS TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Helius Technologies Pte Ltd is seeking a data-centric professional in Singapore to support data quality profiling, metadata governance and risk-focused data reviews. The role involves analyzing data for completeness and accuracy, and ensuring alignment with financial services data models.

Ideal candidates have 1-3 years in banking or financial services, and strong SQL skills, plus exposure to data platforms like Hadoop or PySpark.

Qualifications

• 1-3 years’ experience in Banking or Financial Services, preferably in a Data Management, Data Analyst or Data Engineer role.
• Working experience in Financial Services or Management Consulting, or strong exposure to Banking.
• Good understanding of Financial Products & Processes and the data models for these.
• Proficiency in SQL is a pre-requisite.
• Attention to detail with the capacity for diligent follow-through.
• Knowledge of Data Management frameworks like DAMA, DCAM will be an advantage.
• Experience with data technologies & languages such as Hadoop, Cloudera Data Platform, Python, PySpark, Superset, Teradata would be a plus.

Responsibilities

• Assist in both periodic & ad-hoc Data Quality profiling and dashboarding;
• Review and approve business metadata data;
• Assist in thematic reviews focused on Data & AI risk;
• Conduct data analysis for purpose of surfacing data inconsistencies, and reviewing of data completeness, intended uses and purposes;
• Any other tasks assigned by the supervisor.

Skills

SQL

Data analysis

Data management

Hadoop

Python

PySpark

Superset

Teradata

Tools

Hadoop

Cloudera Data Platform

Python

PySpark

Superset

Teradata

Job description

Helius Technologies Pte Ltd is seeking a data-centric professional in Singapore to support data quality profiling, metadata governance and risk-focused data reviews. The role involves analyzing data for completeness and accuracy, and ensuring alignment with financial services data models.

Ideal candidates have 1-3 years in banking or financial services, and strong SQL skills, plus exposure to data platforms like Hadoop or PySpark.