Description

You design, build, and maintain scalable data pipelines and software applications to support business requirements.

This role is hybrid.

Responsibilities

• Build and optimize large-scale ETL/ELT processes and data architectures using Python, Spark, Kafka, and Hadoop.
• Design and deploy scalable cloud-based data solutions on AWS, Azure, or GCP, including Kubernetes and Docker orchestration.
• Develop and maintain software applications and APIs, implementing test-driven development (TDD) and CI/CD practices.
• Monitor application performance, troubleshoot issues, and improve reliability, scalability, and security for large data volumes.
• Collaborate with product owners and architects to define technical requirements and evaluate emerging technologies.

Required Skills

• 5+ years of progressive experience in software or data engineering with a focus on large-scale data systems.
• Expert-level proficiency in Python and/or Java, with advanced SQL skills.
• Hands-on experience with Apache Spark, Kafka, Hadoop, and NoSQL databases.
• Proven experience designing and deploying scalable cloud data solutions on AWS, Azure, or GCP.
• Strong knowledge of data architecture, ETL/ELT processes, and cloud infrastructure.
• Experience with containerization tools such as Kubernetes and Docker.
• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related field.

Preferred Skills

• Experience implementing test-driven development (TDD) and continuous integration/delivery (CI/CD) pipelines.
• Background in evaluating and adopting emerging technologies to enhance development efficiency.

Key Skills

Education

Any Graduate