Roles and Responsibilities

• Design and implement robust and scalable solutions using Core Java, Spring Boot, Microservices, and REST APIs.
• Leverage Apache Spark to process large datasets, optimize performance, and create efficient data pipelines.
• Integrate applications with AWS services such as S3, ECS/EKS, DynamoDB, Lambda, and Step Functions for scalable and efficient cloud-based solutions.
• Implement ETL patterns and work with Data Lakes, Data Warehouses, and Big Data Engineering to process and manage large datasets.
• Apply design patterns to build maintainable, scalable, and efficient code.
• Work with cross-functional teams to ensure integration and scalability of data solutions and services.

Required Qualifications

• Strong experience in Java, including Spring Boot, Microservices, and REST APIs.
• Hands-on experience with Apache Spark for big data processing.
• Familiarity with AWS technologies such as S3, ECS/EKS, DynamoDB, Lambda, and Step Functions.
• Experience in Data Lakes, ETL processes, and Data Warehousing.
• Ability to design and implement data pipelines using Spark and AWS services.
• Strong understanding of design patterns for software development.
• Experience working with AWS cloud architecture and services.

Preferred Skills/Qualifications

• Experience with Terraform for Infrastructure as Code (IaC).
• Familiarity with Databricks for big data analytics.
• Experience with Snowflake or AWS Data Lake formation for data storage and management.
• Knowledge of Big Data engineering, data lakes, and data warehouse ETL patterns.
• Previous experience working in agile environments.
• Familiarity with DevOps practices and CI/CD pipelines.

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