Data Engineer
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Role details
Tech stack
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Job description
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Design, build, and optimize scalable data pipelines using AWS Glue, Apache Kafka, AWS Lambda, and Step Functions.
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Develop and maintain robust data lakes and data warehouses on Amazon S3.
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Write infrastructure as code using CloudFormation Templates (CFT).
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Collaborate with Data Scientists and ML Engineers to integrate AI/ML models into production-grade data workflows.
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Write efficient, reusable, and testable code in Python, SQL, and PySpark.
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Ensure data quality, governance, and security across all data platforms.
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Monitor and troubleshoot data pipeline performance and reliability.
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Participate in architectural discussions and contribute to cloud strategy and best practices.
Requirements
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7-10+ years of experience in Data Engineering with a strong focus on AWS Cloud
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Proficiency in Python, SQL, and PySpark.
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Hands-on experience with the following
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AWS Glue
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Apache Kafka
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Amazon S3
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AWS Lambda
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AWS Step Functions
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CloudFormation Templates (CFT)/Terraform
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Basic understanding of AI concepts
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Experience with CI/CD tools and DevOps practices in cloud environments.
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Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. * AWS certifications (e.g., AWS Certified Data Analytics, Solutions Architect)
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Experience with other cloud platforms (Azure, GCP)
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Familiarity with containerization (Docker, ECS) and orchestration tools (Airflow, Step functions)
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Knowledge of data governance frameworks and compliance standards
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