Job Description

Data Modelling Analyst

Industry:

Investment & Asset Management

Role Overview

The Data Modelling Analyst will be responsible for designing, developing, and maintaining data models that support investment operations, data warehouse systems, analytics, and digital solutions. This role requires strong hands-on experience in data modelling, cloud databases, and understanding of investment or financial data structures.

Key Responsibilities

Develop conceptual, logical, and physical data models for various platforms, including RDBMS, Operational Data Stores (ODS), data marts, and data lakes (SQL/NoSQL). Design, document, and implement data architecture solutions using relational, dimensional, and NoSQL databases. Translate business and IT requirements into effective data solutions across reporting, analytics, visualization, and machine learning platforms. Perform impact analysis for new requirements and provide accurate estimates for data model changes. Apply normalization techniques to reduce redundancy and improve data integrity. Identify data architecture needs, interfaces to data sources, automated data load mechanisms, and security considerations. Work independently to address project issues, ensure timely delivery, and mitigate risks. Collaborate with BI/Data Engineers to ensure accurate and consistent data models for Data Lake/Data Mart environments. Produce data mapping documentation and support root cause analysis for data-related defects. Optimize and govern existing data architecture to improve query performance and overall efficiency. Support project documentation, reporting, and data warehouse system maintenance.

Required Skills & Experience

Minimum 3 years of hands-on experience in Cloud Architecture (Azure, GCP, AWS) and cloud databases (e.g., Synapse, Databricks, Snowflake, Redshift). Strong experience in data integration techniques (API, streaming, file-based) using DBT, SQL/PySpark, and Python. Proficient in data modelling tools and data warehousing concepts. Strong SQL/NoSQL development skills, including complex queries and stored procedures. Solid understanding of normalization (1NF, 2NF, 3NF, BCNF). Experience with BI and visualization tools (Power BI, Tableau, MicroStrategy, Qlik). Familiar with facilitating data exchange between systems (API, SFTP). Experience working in Agile/Scrum environments. Strong analytical, problem-solving, and troubleshooting abilities for both structured and unstructured data. Excellent written and verbal communication skills.

Education & Additional Requirements

Bachelor's or Master's degree in Computer Science, IT, Engineering, Mathematics, Statistics, or related field. At least 3 years of experience in Data Modelling, Data Engineering, or Solution Design roles. Prior experience in the

financial services or investment industry

is an advantage. Experience in ETL/ELT-intensive projects is preferred. Knowledge of market and investment data is a plus. Self-driven and committed to delivering high-quality results.
Job Type: Full-time

Application Question(s):

Do you have experience in Financial Service industry?
Work Location: In person