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Data Engineer

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Summary

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

  • Design, develop, and maintain data pipelines and ETL/ELT processes using AWS services.

  • Develop and optimize SQL queries for data extraction, transformation, validation, and analysis.

  • Use Python for data processing, automation, and pipeline development.

  • Manage and process data using AWS S3 and AWS Redshift.

  • Develop and maintain ETL workflows using AWS Glue.

  • Configure and manage AWS IAM roles, users, and policies to support secure data access.

  • Monitor data pipelines, jobs, and AWS resources using AWS CloudWatch.

  • Perform data synchronization and ensure consistency across systems.

  • Troubleshoot data pipeline failures, performance issues, and data quality concerns.

  • Implement data validation and reconciliation processes to ensure accuracy and completeness.

  • Collaborate with Data Analysts, Software Engineers, Business Analysts, and other stakeholders to understand data requirements.

  • Maintain technical documentation for data pipelines, processes, and AWS environments.

  • Follow data security, governance, and access control best practices.

Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.

  • 3+ years of experience in Data Engineering or a related role.

  • Strong hands-on experience with SQL and Python.

  • Experience working with AWS S3 and AWS Redshift.

  • Hands-on experience with AWS Glue for ETL/data processing.

  • Knowledge of AWS IAM, including Roles, Users, and Policies.

  • Experience with AWS CloudWatch for monitoring and troubleshooting.

  • Experience with data synchronization, ETL/ELT, and data pipeline development.

  • Strong understanding of data processing, transformation, and validation.

  • Strong analytical and problem-solving skills.

  • Good communication and collaboration skills.

Preferred Skills

  • Experience with additional AWS data services such as AWS Lambda, Athena, RDS, or Step Functions.

  • Experience with Apache Spark/PySpark.

  • Knowledge of data warehousing and dimensional modeling.

  • Experience with CI/CD and Git.

  • Knowledge of data quality and data governance concepts.

  • 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

See also

Data Engineering jobs by country — openings, pay and top skills →

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