The role involves working with advanced AWS technologies to design, build, and maintain scalable data pipelines and architectures. The ideal candidate will have strong expertise in SQL, Python/PySpark, and key AWS services including Glue, Step Functions, EMR (EC2), S3, Lambda, and Athena. The position is focused on leveraging DevOps practices for smooth delivery and deployment.

Key Responsibilities:

• Develop and manage data pipelines using Python/PySpark and AWS Glue.
• Implement AWS Step Functions and EMR for orchestrating and processing data workflows.
• Work with S3 for efficient data storage solutions.
• Leverage Lambda and Athena for real-time data queries and analytics.
• Apply DevOps principles to optimise data engineering processes and streamline delivery.
• Collaborate with cross-functional teams to align data engineering efforts with business objectives.

Skills & Experience Required:

• Proficiency in SQL and Python/PySpark for data processing and analysis.
• Hands-on experience with key AWS services (Glue, Step Functions, EMR, S3, Lambda, Athena).
• Knowledge of DevOps practices and tools for CI/CD in data engineering projects.
• Strong problem-solving skills and ability to work within an agile development environment.
• Prior experience in data engineering roles with a focus on cloud-based architectures.

Additional Criteria:

• Experience within the insurance industry is advantageous.
• Ability to work independently as well as part of a collaborative team.
• Strong communication skills for stakeholder interaction and requirement gathering.

Qualifications/Certification:

• A degree in Computer Science, Information Systems, Business Administration, Commerce, or an equivalent field.
• Relevant certifications in AWS, data engineering, or DevOps are highly desirable.

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