Data Analytics Engineer (Bank / Finance, BI / ETL / Data Modelling, 40-46K)

Swing Consulting Ltd.

Hong Kong

On-site

HKD 390,600 - 502,200

Full time

14 days+
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Benefits offered by this job

Salary depending on exp
Annual leave 10-20 days
5-day work week
Energetic working environment

Job summary

Swing Consulting Ltd. is seeking a Data Analytics Engineer for a banking/finance client in Hong Kong. You will translate business needs into scalable analytics models and ETL designs, lead workshops, and design data storage structures to support growth.

You will work with cross-functional teams, implement Power BI/SSAS solutions, and ensure data quality and reconciliation checks, while documenting functional requirements and technical workflows in clear language.

Qualifications

  • Bachelor’s degree in Computer Science, Data Engineering, Mathematics, Statistics, Business, or a related field.
  • 5+ years in IT, including 2+ years in BI, data migration, or data warehouse pipelines, and 3+ years in Oracle or SQL Server development.
  • Strong background in data modeling (Star/Snowflake), quality metrics, DDL/DML, and PL/SQL Stored Procedures.
  • Hands-on experience modeling, deploying, and tuning Power BI and SSAS servers, including RLS and M scripting.
  • Knowledge of Hadoop, Python, Java Spring Boot, Docker, or OCP is a plus.
  • Fluent in written and spoken English and Chinese (Mandarin and Cantonese).
  • Proactive problem solver with strong multitasking abilities.

Responsibilities

  • Translate business needs into scalable analytics models and ETL designs with cross-functional teams.
  • Lead workshops to define requirements, align expectations, and resolve client inquiries.
  • Design storage structures and reconciliation checks; standardize exception controls for easy troubleshooting.
  • Author clear documentation for functional and non-functional solution requirements.
  • Architect adaptable data models that support growth while minimizing change risk and costs.
  • Evaluate new data sources using structured frameworks to assess integration impact.
  • Resolve data discrepancies and convert business logic into scalable technical workflows.

Skills

Power BI
SSAS
PL/SQL
RLS
M scripting
Python
Docker
Java Spring Boot
Hadoop
Bilingual English/Chinese

Education

Bachelor’s degree in Computer Science, Data Engineering, Mathematics, Statistics, Business, or related field

Tools

Oracle
SQL Server
Power BI
SSAS
Hadoop

Job description

SW9018 |22 Jul 2026 Data Analytics Engineer (Bank / Finance, BI / ETL / Data Modelling, 40-46K)

  • Translate business needs into scalable analytics models and ETL designs with cross-functional teams.
  • Lead workshops to define requirements, align expectations, and resolve client inquiries.
  • Design storage structures and reconciliation checks; standardize exception controls for easy troubleshooting.
  • Author clear documentation for functional and non-functional solution requirements.
  • Architect adaptable data models that support growth while minimizing change risk and costs.
  • Evaluate new data sources using structured frameworks to assess integration impact.
  • Resolve data discrepancies and convert business logic into scalable technical workflows.
  • Bachelor’s degree in Computer Science, Data Engineering, Mathematics, Statistics, Business, or a related field.
  • 5+ years in IT, including 2+ years in BI, data migration, or data warehouse pipelines, and 3+ years in Oracle or SQL Server development.
  • Strong background in data modeling (Star/Snowflake), quality metrics, DDL/DML, and PL/SQL Stored Procedures.
  • Hands-on experience modeling, deploying, and tuning Power BI and SSAS servers, including RLS and M scripting.
  • Knowledge of Hadoop, Python, Java Spring Boot, Docker, or OCP is a plus.
  • Fluent in written and spoken English and Chinese (Mandarin and Cantonese).
  • Proactive problem solver with strong multitasking abilities.
  • Benefits:
  • 35-45K Depends on Experience
  • 10-20 Days Annual Leave
  • 5-day Work Week
  • Friendly and Energetic Working Environment

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