Description

Key Skills: Java, Apache Spark, Kafka, Big Data, Hadoop, Spring Boot, Microservices, Data Migration, Sybase IQ, Docker

Good to Have Skills: Experience with cloud-native data services on platforms like AWS (EMR, S3, Glue), Google Cloud Platform (Dataflow, BigQuery), or Azure. Knowledge of containerization technologies and OpenShift. Experience using AI-powered development tools (GitHub Copilot, Claude, Devin) to accelerate development. Knowledge of financial systems, particularly in trade processing, accounting, risk, or sub-ledger functions.

Roles & Responsibilities:

• Define the end-to-end architectural vision and technical roadmap for migrating from Sybase IQ to a modern Big Data platform, ensuring solutions are scalable, resilient, and secure
• Lead the design, development, and deployment of robust, large-scale data processing pipelines using technologies like Apache Spark, Kafka, and distributed data stores
• Develop and execute a comprehensive, phased strategy for migrating petabytes of historical and transactional data from Sybase IQ, ensuring data integrity, minimal downtime, and zero business disruption
• Oversee the design and development of Java-based microservices that interact with the new data platform, ensuring seamless integration with the broader Oasys application ecosystem
• Lead, inspire, and mentor a high-performing team of Java and Big Data engineers while fostering a culture of engineering excellence, innovation, and accountability
• Partner with global business leaders, product owners, and other senior technology managers to define requirements, manage expectations, and deliver solutions that drive significant business value
• Remain deeply technical and contribute to coding, design, and architectural decisions, leading by example in hands-on development work

Experience Required: 10+ years of progressive experience in professional software engineering, with at least 3 years in a technical leadership or architect role. Proven track record of designing and building complex, high-performance, scalable server-side applications using Java. Deep, hands-on experience with the Big Data ecosystem, including mastery of Apache Spark, Hadoop (HDFS), and real-time data streaming with Kafka. Extensive experience with relational databases, data modeling, and data warehousing concepts.

Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field

Key Skills

Education

Any Graduate