We are seeking a skilled Big Data Developer with strong expertise in AWS Cloud, Hadoop Ecosystem, and PySpark. The ideal candidate will be responsible for designing, developing, and supporting scalable data engineering solutions while working closely with business and technology teams to deliver enterprise-grade data platforms.
Key Responsibilities:- Design, develop, test, and support large-scale Big Data and data engineering solutions.
- Build and maintain scalable data pipelines using PySpark and Hadoop technologies.
- Gather business requirements and convert them into technical specifications and data solutions.
- Develop and optimize ETL/ELT workflows for structured and unstructured data processing.
- Implement cloud-native data solutions leveraging AWS services.
- Participate in architecture discussions, effort estimation, and solution design activities.
- Ensure adherence to coding standards, security guidelines, and development best practices.
- Monitor and troubleshoot data processing workflows and production issues.
- Collaborate with cross-functional teams, business stakeholders, and project managers.
- Contribute to CI/CD implementation and automation for data engineering projects.
Required Skills & Qualifications:- 6–8 years of experience in Big Data and Data Engineering.
- Strong hands-on experience with PySpark and Hadoop Ecosystem.
- Experience with AWS Cloud services including EKS, S3, EMR, Glue, and Lambda.
- Proficiency in Scala or Python for data processing and automation.
- Strong understanding of distributed computing and large-scale data processing.
- Experience designing and implementing enterprise data pipelines.
- Knowledge of Snowflake and modern cloud data warehousing concepts.
- Understanding of CI/CD pipelines and DevOps practices.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management abilities.