AWS Data Engineer

2 weeks ago

hyderabad, India Talent Worx Full time

Senior AWS Data EngineerOverview:We are seeking experienced AWS Data Engineers to design, implement, and maintain robust data pipelines and analytics solutions using AWS services. The ideal candidate will have a strong background in AWS data services, big data technologies, and programming languages.Exp- 3 to 7 years Location- Bangalore, Pune, Hyderabad, Coimbatore, Delhi NCR, Mumbai RequirementsKey Responsibilities:1. Design and implement scalable, high-performance data pipelines using AWS services2. Develop and optimize ETL processes using AWS Glue, EMR, and Lambda3. Build and maintain data lakes using S3 and Delta Lake4. Create and manage analytics solutions using Amazon Athena and Redshift5. Design and implement database solutions using Aurora, RDS, and DynamoDB6. Develop serverless workflows using AWS Step Functions7. Write efficient and maintainable code using Python/PySpark, and SQL/PostgrSQL8. Ensure data quality, security, and compliance with industry standards9. Collaborate with data scientists and analysts to support their data needs10. Optimize data architecture for performance and cost-efficiency11. Troubleshoot and resolve data pipeline and infrastructure issuesRequired Qualifications:1. bachelor's degree in computer science, Information Technology, or related field2. Relevant years of experience as a Data Engineer, with at least 60% of experience focusing on AWS3. Strong proficiency in AWS data services: Glue, EMR, Lambda, Athena, Redshift, S34. Experience with data lake technologies, particularly Delta Lake5. Expertise in database systems: Aurora, RDS, DynamoDB, PostgreSQL6. Proficiency in Python and PySpark programming7. Strong SQL skills and experience with PostgreSQL8. Experience with AWS Step Functions for workflow orchestrationTechnical Skills:- AWS Services: Glue, EMR, Lambda, Athena, Redshift, S3, Aurora, RDS, DynamoDB, Step Functions- Big Data: Hadoop, Spark, Delta Lake- Programming: Python, PySpark- Databases: SQL, PostgreSQL, NoSQL- Data Warehousing and Analytics- ETL/ELT processes- Data Lake architectures- Version control: Git- Agile methodologies

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