Data Analyst at TMGM

Sydney, New South Wales, Australia -

Full Time

Start Date

Immediate

Expiry Date

21 Jun, 26

Salary

0.0

Posted On

23 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, ClickHouse, Kafka, RabbitMQ, Data Analysis, PnL Reporting, Trading Analytics, Data Quality, Data Modeling, SQL Optimization, Data Visualization

Industry

Financial Services

Description

About The Company TMGM is one of the fastest-growing CFD and Forex brokers in the Asia-Pacific region, trusted by over 150,000 clients globally. With a strong focus on innovation, client satisfaction, and regulatory compliance, we continue to expand our presence across international markets. About The Role The Data Analyst (Trading & PnL) will be responsible for transforming high-velocity data into the financial narratives that drive our trading strategies. By navigating our real-time pipelines—built on Kafka, RabbitMQ, and ClickHouse—you will ensure that PnL reports and trading analytics are accurate, timely, and insightful. This role sits at the intersection of engineering and finance, requiring a blend of technical rigour and market understanding. Key Responsibilities: Develop and maintain automated PnL reporting frameworks that pull from real-time data streams. Conduct deep-dive trading analytics to identify execution patterns, slippage, and market impact. Write and optimise complex SQL queries in ClickHouse to handle large-scale financial datasets efficiently. Collaborate with stakeholders to define and implement key performance indicators (KPIs) for various trading desks. Monitor data quality and integrity across the pipeline to ensure financial reporting remains compliant and accurate. Use Python to build robust data processing scripts that automate repetitive analytical tasks. Design data models and schemas that specifically support high-frequency reporting and business objectives. Requirements: Bachelor’s or Master’s degree in Finance, Economics, Computer Science, or a related quantitative field. Prior experience working within the finance or fintech industry, with an understanding of financial instruments or trading data. Advanced SQL knowledge and experience with OLAP databases like ClickHouse. Strong programming skills in Python for data manipulation and automation tasks. Experience with data visualisation tools to represent real-time data effectively. Ability to convey technical findings clearly to both technical and non-technical stakeholders. Detail-oriented mindset with a focus on data accuracy and compliance with governance policies. Hybrid working arrangement - 2 Days of remote work per week Opportunities for enriching career growth, including exposure to regional contexts Complimentary snacks and beverages available in the office pantry Healthcare coverage (medical, dental, optical), gym benefits Flexibility in smart casual dress code Young, vibrant and open work culture

Responsibilities

The Data Analyst will be responsible for transforming high-velocity data into financial narratives that drive trading strategies, focusing on PnL reports and trading analytics accuracy using real-time pipelines. Key tasks include developing automated PnL reporting frameworks, conducting deep-dive trading analytics, and writing complex SQL queries in ClickHouse.