AWS Data Engineer: Scalable Pipelines & Snowflake

TymblHub; Hinoba-an; On-site; PHP 1,000,000 - 1,500,000; Full time

Job summary

PwC is seeking an experienced AWS Data Engineer to design, develop and maintain scalable data pipelines and cloud-based platforms. The role requires 4-8 years of hands-on experience with AWS, Snowflake, Airflow, Python, PySpark and SQL to support data warehousing, ETL/ELT, and performance optimization.

You will collaborate with data architects, analysts and application teams to build reliable data solutions, ensure data quality, and enable data-driven decision making across client engagements.

Qualifications

• 4–8 years of hands-on AWS data engineering experience.
• Strong knowledge of AWS services, Snowflake, Airflow, Python, PySpark, and SQL.
• Experience with data warehousing, ETL/ELT, data modeling and performance tuning.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using AWS services.
• Build and orchestrate data pipelines using Apache Airflow, including DAG development and monitoring.
• Develop data processing with Python and PySpark and optimize SQL transformations.
• Design Snowflake data warehouse solutions and optimize performance and costs.

Tools

AWS

Snowflake

Apache Airflow

Python

PySpark

SQL

Job description

PwC is seeking an experienced AWS Data Engineer to design, develop and maintain scalable data pipelines and cloud-based platforms. The role requires 4-8 years of hands-on experience with AWS, Snowflake, Airflow, Python, PySpark and SQL to support data warehousing, ETL/ELT, and performance optimization.

You will collaborate with data architects, analysts and application teams to build reliable data solutions, ensure data quality, and enable data-driven decision making across client engagements.