Tech - Data Engineer

Job Purpose

As a Data Engineer, you will design, build, and optimize scalable data platforms that support trading and business functions across global markets. You will architect high-performance data systems, develop robust ETL pipelines, and enable efficient processing of large-scale datasets while ensuring reliability, scalability, and data governance standards.

Responsibilities

• Design, develop, and maintain large-scale data platforms and processing systems that support trading and business operations.
• Build and optimize data ingestion, transformation, and storage solutions to improve performance, reliability, and operational efficiency.
• Develop, manage, and enhance ETL pipelines capable of handling large-volume, high-frequency datasets.
• Design and implement fault-tolerant, scalable, and distributed data architectures using modern engineering frameworks and technologies.
• Leverage Java, Python, Kafka, and microservices-based architectures to build high-performance data engineering solutions.
• Drive data governance, quality, and platform best practices while ensuring data consistency and integrity across systems.
• Automate operational processes, optimize existing applications, and continuously improve system scalability and maintainability.
• Collaborate closely with trading, technology, and business teams while mentoring junior engineers and contributing to the growth of the engineering organization.

Key Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical discipline with an understanding of financial markets and trading concepts.
• 4+ years of experience in data engineering, data platform development, or large-scale data processing environments.
• Strong programming skills in Java and Python with experience building enterprise-grade applications and services.
• Experience working with microservices architectures, Spring Framework, and distributed systems.
• Strong understanding of ETL development, data warehousing concepts, and large-scale data pipeline design.
• Experience with messaging and streaming technologies such as Kafka and automation using shell scripting.
• Hands-on experience with relational and analytical databases, preferably ClickHouse and PostgreSQL.
• Knowledge of CI/CD practices and tools such as Jenkins, with a focus on automation and deployment reliability.
• Experience designing scalable, fault-tolerant, and high-performance systems capable of handling large datasets.
• Exposure to trading firms, capital markets, or international exchange data environments will be an added advantage.
• Strong analytical, problem-solving, and communication skills with the ability to work effectively across cross-functional teams.
• Demonstrated attention to detail, process orientation, continuous learning mindset, and the ability to mentor junior team members.