Cloud Data Engineer

A Leading Financial Technology Firm is seeking a delivery-minded Cloud Data Engineer to strengthen fraud detection and digital protection platforms.

The Cloud Data Engineer must combine robust Java and Python backend programming with hands-on capabilities across Snowflake, SQL, distributed data stores, and AWS cloud architectures.

Key Responsibilities

• Build, optimize, and maintain scalable software applications and data pipelines supporting identity proofing and fraud prevention systems.
• Develop high-performance backend modules utilizing Java, object-oriented Python, and advanced SQL queries.
• Design and manage distributed data storage and warehousing workflows across Snowflake, Yugabyte, and Aerospike.
• Engineer robust ETL and ELT data processing pipelines for both structured and unstructured customer dataset feeds.
• Deploy, maintain, and monitor containerized microservices across Docker and Kubernetes clusters on AWS.
• Implement automated build and deployment pipelines leveraging continuous integration platforms such as Jenkins and Terraform.
• Integrate real-time messaging frameworks and event-driven architectures utilizing Apache Kafka.
• Collaborate actively with fraud risk analysts, security specialists, and cross-functional Agile engineering pods.

Requirements and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a related field.
• 3-5 Years of professional software development experience specializing in data warehousing, SQL, and Java backend solutions.
• Demonstrated programming proficiency in Java and Python with applied object-oriented design principles.
• Hands-on experience working with Snowflake, Yugabyte, AWS cloud deployment (S3, compute services), and relational databases.
• Familiarity with event-driven architectures (Kafka), CI/CD pipelines (Jenkins, Git), and container systems (Docker, Kubernetes).