AWS Data Engineer
About Xebia
Xebia is a trusted advisor in the modern era of digital transformation, serving hundreds of leading brands worldwide with end-to-end IT solutions. The company has experts specializing in technology consulting, software engineering, AI, digital products and platforms, data, cloud, intelligent automation, agile transformation, and industry digitization. In addition to providing high-quality digital consulting and state-of-the-art software development, Xebia has a host of standardized solutions that substantially reduce the time-to-market for businesses.
Xebia also offers a diverse portfolio of training courses to help support forward-thinking organizations as they look to upskill and educate their workforce to capitalize on the latest digital capabilities. The company has a strong presence across 16 countries with development centres across the US, Latin America, Western Europe, Poland, the Nordics, the Middle East, and Asia Pacific.
We are seeking an experienced AWS Data Engineer to design and implement scalable data pipelines and solutions using AWS cloud technologies. You will be responsible for building robust data infrastructure to support analytics, reporting, and machine learning workloads.
Key Responsibilities:
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Design and develop ETL/ELT pipelines using AWS-native tools
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Build scalable data processing systems using AWS Glue, Lambda, Step Functions, and Athena
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Work with S3, Redshift, and RDS for data storage, warehousing, and transformation
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Develop and maintain Python and SQL scripts for data manipulation and automation
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Handle real-time and batch data ingestion using services like Kinesis or Kafka
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Collaborate with data scientists, analysts, and engineering teams to support business use cases
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Monitor data workflows, ensure data quality, and troubleshoot pipeline issues
Required Skills:
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Strong hands-on experience with AWS data services: Glue, S3, Redshift, Lambda, Athena
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Proficiency in Python and advanced SQL
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Experience with workflow orchestration tools like Airflow or Step Functions
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Familiarity with data lake and data warehouse architectures on AWS
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Good understanding of data security, IAM roles, and cloud best practices
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Strong problem-solving and collaboration skills
Nice to Have:
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Experience with Kinesis, Kafka, or other streaming platforms
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Exposure to Terraform/CloudFormation for infrastructure as code
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Familiarity with Spark or EMR for big data processing
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Experience with data cataloging, governance, or ML workflows
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