DataOps Engineer

LMAX Group is looking for a highly skilled and passionate Data Operations Engineer/Developer to join our team and help build and scale our data processing infrastructure. In this role, you'll develop high-performance data pipelines, real-time streaming systems, and robust data architectures that power LMAX's growth and Business Intelligence initiatives.

You will work with the wider technology and business teams to continuously improve the quality of data that drives our decision making within the Forex and digital currency trading and custody solutions.

Main Duties & Responsibilities:

• Design, develop, and maintain scalable data infrastructure to support our BI/MI workloads.
• Manage and optimize data pipelines, ETL/ELT processes, and data warehousing solutions.
• Ensure high availability, performance, and reliability of our data platforms and services.
• Conduct code reviews, mentoring others, and enforce best practices in data engineering.
• Diagnose and resolve data quality issues, ensuring accuracy, efficiency, and security.
• Maintain the confidentiality, integrity and availability of LMAX information assets.

Essential Experience:

• 3+ years of experience in data engineering or backend software development

• Proficiency in Python or Java for data retrieval and pipeline development

• Experience with IaC tools such as Terraform or Ansible for deployment and infrastructure management

Hands-on experience with;

• ETL/ELT orchestration and pipeline tools (Airflow, Airbyte, DBT, etc.)
• Data warehousing tools and platforms (Snowflake, Iceberg, etc.)
• Real-time data streaming platforms (Kafka, Redpanda, Active/RabbitMQ, etc.)
• SQL databases, particularly MySQL

Desired Experience:

• Experience with cloud-based services, particularly AWS
• Proven ability to manage stakeholders, their expectations and explain complex problems or solutions in a manner suitable for the audience.
• Knowledge of data governance and metadata management
• Knowledge of data security best practices and compliance requirements

Success Looks Like:

• Safely implement controls to enable self-service of Data for other teams such as Data Scientists and the Business
• Be a driving force within the team, leveraging automation and tooling.
• A measurable increase of useable data sources feed into reports
• Demonstrate performant and resilient data infrastructure than can scale with the needs of the Group
• Receive positive feedback from technology teams and other business stakeholders

• 25 days of holiday
• Bonus
• Pension contribution

• Private medical, dental, and vision coverage
• Life assurance
• Critical illness cover
• Wellness contribution program with access to ClassPass
• Plumm Platform
• Five volunteering days
• Give as You Earn initiative
• Learning and development programs
• Electric Vehicle Scheme
• Cycle to Work Scheme
• Season Ticket Loan