Job Title: Data Engineer – AWS Glue, Airflow, Python, Snowflake, Informatica

About the Role:

Seeking a highly skilled and hands-on Data Engineer with deep experience in building scalable data ingestion pipelines and ETL frameworks using AWS Glue, Apache Airflow, Python, and Snowflake. The ideal candidate will also have strong exposure to Informatica and enterprise-grade data integration solutions. This is a critical role that involves designing, building, and maintaining robust Ingestion patterns and workflows.

Key Responsibilities:

 Design and implement scalable, reusable data ingestion patterns and ETL pipelines using AWS Glue and Python.

 Develop orchestration workflows using Apache Airflow to manage complex data dependencies and schedules.

 Build and maintain data integration frameworks leveraging Snowflake for cloud data warehousing and Informatica for legacy integration needs.

 Collaborate with data architects, analysts, and business stakeholders to gather requirements and deliver high-quality data solutions.

 Optimize and troubleshoot ETL performance issues, ensuring data accuracy, quality, and integrity.

 Ensure adherence to data governance, security, and compliance standards.

 Automate data validation and quality checks as part of the pipeline development process.

 Document data flow processes and technical specifications.

Required Qualifications:

 2 to 5 years of experience in data engineering or related roles.

 Hands-on expertise with AWS Glue (ETL jobs, crawlers, workflows) .

 Strong programming skills in Python , with experience building modular, testable ETL code.

 Proficient in Apache Airflow for workflow orchestration and automation.

 Solid experience working with Snowflake – data modeling, loading strategies, performance tuning.

 Good understanding and practical experience with Informatica PowerCenter or Informatica Cloud .

 Familiarity with AWS services like S3, Lambda, Athena, CloudWatch, IAM.

 Strong knowledge of SQL and experience in building performant queries.

 Exposure to CI/CD practices for data pipelines (e.g., using Git, Jenkins, etc.).

 Excellent communication and collaboration skills.