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Tech Stack
Tools & technologiesAmazon RedshiftApacheAWSETLPythonScalaSparkSQL
About the role
Key responsibilities & impact- Design, develop and implement data solutions on AWS using Glue, Spark and Redshift
- Collaborate with data engineers and data scientists to understand data requirements and translate them into scalable data pipelines
- Build and manage ETL processes using AWS Glue to extract, transform and load data from multiple sources
- Optimize data processing workflows in Apache Spark to ensure efficient data handling and analysis
- Develop and maintain data models and schemas in Amazon Redshift to support reporting and analytics
- Monitor and troubleshoot data pipelines to ensure data quality and integrity
- Document data processes, architecture and best practices for knowledge sharing and compliance.
Requirements
What you’ll need- Bachelor's degree in Information Systems, Computer Science, Data Engineering or a related field
- Advanced/Fluent English - C2 (there will be contact with an international client)
- Proven experience developing on AWS with a focus on Glue, Spark and Redshift
- Proficiency in programming languages such as Python or Scala for data processing
- Strong expertise in Amazon SNS: topic management, subscriptions, message publishing, AWS integration, security, error handling and monitoring
- Solid understanding of data warehousing concepts and best practices
- Experience with SQL and database management systems is required.
Benefits
Comp & perks- Meal allowance
- Meal voucher
- Transportation allowance
- Health insurance
- Dental coverage
- Corporate University
- Other educational benefits
- Wellhub
- Profit-sharing (PLR)
- And more
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AWSGlueSparkRedshiftETL processesPythonScalaSQLdata warehousingdata modeling
Soft Skills
collaborationcommunicationtroubleshootingdocumentationknowledge sharing
