Let our industry specialists listen to your aspirations and present your story to the organisations in Hong Kong that fit you the best as we collaborate to write the next chapter of your successful career.
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Let our industry specialists listen to your aspirations and present your story to the organisations in Hong Kong that fit you the best as we collaborate to write the next chapter of your successful career.
We understand that no two organisations are the same. Find out more about how we've customised our recruitment offerings to help companies in Hong Kong meet their needs.
My client is looking for an experienced Senior Data Analytics Engineer to join their team in shaping the new modern data stack encompassing data pipelines, modelling, and analytics reporting in financial services.
Responsibilities
Design, build, and maintain enterprise data models to support analytic needs across strategies. In financial EDM tools and/or Cloud warehouse such as Snowflake
Design, develop, and support reports and dashboards within an enterprise reporting environment to support data analysis and AI.
Design, build, and optimize data pipelines that extract, load, and transform (ELT) data from different financial services systems and fund administrators into data lake and data warehouse.
Integrate diverse data sources from complex portfolio management systems and financial management systems into a unified data ecosystem.
Transform and cleanse raw data into structured and usable formats, ensuring data quality and consistency using data tools such as (DBT, Python, ADF)
Design and implement automated data flow for ongoing data quality and governance processes to support data operations
Provide data analytics requirements and solution design to create modern data products and experiences.
Empower the business with robust reporting and analytics capabilities.
Requirements
8+ years relevant experience as an analytics engineer
3+ years in Financial Services industry (fund house or asset management preferred)
Bachelor’s degree in computer science, engineering, or related field
In-depth knowledge of data analytics and engineering principles and best practices
Strong in SQL and Python to handle complex transformation and queries
Experience with cloud platforms such as Azure, AWS
Experience with coding in Python / C# / Java
Experience in using VS Code, GIT, work in a DevOps and DataOps environment
Confident in working with tools such as Snowflake, Databricks, DBT, Anaplan, PowerBI, Power Query, M, DAX, Tableau, Airflow
Flexible with strategic mindset and focus on delivering quality solutions.
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