Designs, builds, and optimizes scalable data platforms, distributed systems, and high-volume ETL pipelines supporting trading and business operations. Develops solutions using Java, Python, Kafka, microservices, and modern databases while ensuring reliability, governance, data quality, and performance. Automates operational processes, improves application scalability, collaborates with trading and technology teams, and mentors junior engineers.
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.
- 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.
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