Data Engineer
NewBe an early applicantSummary
Data Engineer who designs, builds, and maintains data pipelines and ETL/ELT workflows on AWS, writing SQL and Python to extract, transform, and validate data across systems. Core stack includes AWS S3, Redshift, Glue, IAM, and CloudWatch, with a focus on data quality, security, and troubleshooting.
Key Responsibilities
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Design, develop, and maintain data pipelines and ETL/ELT processes using AWS services.
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Develop and optimize SQL queries for data extraction, transformation, validation, and analysis.
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Use Python for data processing, automation, and pipeline development.
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Manage and process data using AWS S3 and AWS Redshift.
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Develop and maintain ETL workflows using AWS Glue.
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Configure and manage AWS IAM roles, users, and policies to support secure data access.
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Monitor data pipelines, jobs, and AWS resources using AWS CloudWatch.
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Perform data synchronization and ensure consistency across systems.
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Troubleshoot data pipeline failures, performance issues, and data quality concerns.
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Implement data validation and reconciliation processes to ensure accuracy and completeness.
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Collaborate with Data Analysts, Software Engineers, Business Analysts, and other stakeholders to understand data requirements.
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Maintain technical documentation for data pipelines, processes, and AWS environments.
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Follow data security, governance, and access control best practices.
Qualifications
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Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
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3+ years of experience in Data Engineering or a related role.
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Strong hands-on experience with SQL and Python.
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Experience working with AWS S3 and AWS Redshift.
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Hands-on experience with AWS Glue for ETL/data processing.
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Knowledge of AWS IAM, including Roles, Users, and Policies.
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Experience with AWS CloudWatch for monitoring and troubleshooting.
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Experience with data synchronization, ETL/ELT, and data pipeline development.
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Strong understanding of data processing, transformation, and validation.
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Strong analytical and problem-solving skills.
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Good communication and collaboration skills.
Preferred Skills
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Experience with additional AWS data services such as AWS Lambda, Athena, RDS, or Step Functions.
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Experience with Apache Spark/PySpark.
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Knowledge of data warehousing and dimensional modeling.
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Experience with CI/CD and Git.
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Knowledge of data quality and data governance concepts.
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Experience working in an Agile/Scrum environment.
Key Skills
Data Engineering | SQL | Python | AWS S3 | AWS Redshift | AWS Glue | AWS IAM | AWS CloudWatch | Data Synchronization | ETL/ELT | Data Pipelines | Data Warehousing | Data Processing | Data Validation | AWS