Data Engineer (AWS)

About the Role

We are looking for a highly skilled Data Engineer with strong AWS cloud expertise to design, build, and maintain scalable data pipelines and data platforms. The ideal candidate will have experience working with large-scale datasets, cloud-based data solutions, ETL/ELT processes, and modern data engineering technologies.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data solutions on AWS cloud platforms.
• Develop and manage data lakes and data warehouses for analytics and reporting.
• Integrate data from multiple sources, ensuring data quality, consistency, and reliability.
• Implement data modeling, transformation, and validation processes.
• Optimize data processing jobs for performance, scalability, and cost efficiency.
• Collaborate with business stakeholders, analysts, and data scientists to understand data requirements.
• Monitor, troubleshoot, and resolve data pipeline and infrastructure issues.
• Ensure data governance, security, and compliance standards are followed.
• Create and maintain technical documentation for data architecture and processes.

Required Qualifications

• 4+ years of experience in Data Engineering.
• Strong hands-on experience with AWS services such as S3, Glue, Redshift, EMR, Lambda, Athena, IAM, and RDS.
• Proficiency in SQL and data modeling concepts.
• Strong programming skills in Python or PySpark.
• Experience building and managing ETL/ELT pipelines.
• Hands-on experience with big data technologies such as Spark, Hadoop, or Databricks.
• Experience with workflow orchestration tools such as Apache Airflow.
• Strong understanding of data warehousing and data lake architectures.
• Experience with version control systems such as Git.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field

Preferred Qualifications

• AWS Certified Data Engineer, Solutions Architect, or related AWS certification.
• Experience with Snowflake, Databricks, or similar cloud data platforms.
• Knowledge of real-time data processing frameworks such as Kafka or Kinesis.
• Experience working with CI/CD pipelines and DevOps practices.
• Exposure to machine learning data pipelines and analytics platforms.
• Experience working in Agile/Scrum environments.