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Senior Data Engineer

TMGM Open · verified Oct 24, 2026
On-site Sydney Full-time Senior Data Engineering

At a glance

Senior Data Engineering role at TMGM. Sydney · full-time.

Pay not stated Data Engineer salary

RoleData Engineering
SenioritySenior
LocationSydney
WorkplaceOn-site
EmploymentFull-time
PostedMar 3, 2026 · 7mo ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Shape resilient ETL and ELT pipelines that can scale with demanding data workloads
  • Set up Kafka and RabbitMQ streaming so data is available in under a second
  • Tune ClickHouse schemas, indexes and queries for large financial datasets
  • Run cloud data services with security, governance, monitoring and automated recovery controls
  • Guide engineers through code reviews and technical coaching, while aligning data plans with senior leaders

What you bring

  • A degree in computer science, engineering or a related discipline
  • Hands-on data engineering experience building ETL workflows in cloud environments
  • Finance or trading technology experience handling live market or transaction data
  • Strong Python and SQL skills for building maintainable, scalable data pipelines

Who this fits

This senior technical leadership role suits someone who can guide engineers and explain complex technical choices to non-technical stakeholders. The position is based onsite in Sydney, with two remote-work days available each week.

From the employer

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

As a Senior Data Engineer, you will be a technical leader responsible for the architecture, scalability, and reliability of our high-throughput, real-time data ecosystem. You will oversee the evolution of our data infrastructure, leveraging Kafka, RabbitMQ, Airflow, and ClickHouse to power mission-critical financial analytics. Your role is to bridge the gap between complex business requirements and high-performance engineering, ensuring our data pipelines can handle the rigours of real-time financial data processing.

Requirements

Key Responsibilities:

  • Lead the design and evolution of highly scalable, fault-tolerant ETL/ELT pipelines.
  • Dive the strategy for real-time messaging and stream processing using Kafka and RabbitMQ to ensure sub-second data availability.
  • Act as the subject matter expert for ClickHouse, optimising complex schema designs, indexing strategies, and query performance for large-scale financial datasets.
  • Oversee the deployment of data services within cloud environments, implementing advanced security protocols and data governance standards essential for the finance industry.
  • Collaborate with senior leadership to align data strategy with business objectives. Mentor data engineers through code reviews and technical guidance.
  • Implement advanced monitoring and automated recovery systems to ensure the integrity and quality of high-stakes financial data.

Requirements:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Proven experience in data engineering, with a strong background in designing and implementing ETL processes within cloud environments.
  • Experience within the Finance or Trading technology sector, with a proven track record of handling real-time market or transactional data.
  • Strong programming skills in Python, with experience in developing robust, maintainable, and scalable data processing pipelines.
  • Extensive SQL knowledge and experience.
  • Excellent problem-solving skills and the ability to work collaboratively in a team environment.
  • Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Benefits

  • 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
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.