We are seeking a skilled Data Engineer with strong AWS experience to design, develop, and optimize data pipelines and architectures. The ideal candidate will have a solid background in data engineering, ETL processes, and cloud services, particularly within the AWS ecosystem.

Responsibilities:

• Design and implement scalable data pipelines using AWS services (e.g., S3, Glue, Redshift, EMR, Lambda, Athena).

• Build and maintain robust ETL/ELT processes for ingesting structured and unstructured data from various sources.

• Optimize performance and reliability of data workflows.

• Collaborate with data scientists, analysts, and business teams to understand data requirements.

• Develop and maintain data models and database solutions.

• Ensure data quality, security, and compliance with best practices.

• Troubleshoot data pipeline issues and perform root cause analysis.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.

• 3–5+ years of experience as a Data Engineer.

• Hands-on experience with AWS data services: Glue, S3, Redshift, Athena, Lambda, and Step Functions.

• Strong SQL skills and experience with relational and NoSQL databases (e.g., PostgreSQL, DynamoDB).

• Proficiency in Python, PySpark, or Scala for data transformation and scripting.

• Experience with data pipeline orchestration tools (e.g., Apache Airflow, AWS Step Functions).

• Familiarity with CI/CD practices and tools (e.g., Git, Jenkins, AWS CodePipeline).

• Strong understanding of data warehousing, data modeling, and big data technologies.