Python AWS

Python AWS Data Engineer

Required Experience

7 years of relevant professional experience in Data Engineering, Cloud Data Engineering, Software Engineering focused on Data, or Data Platforms.

Strong hands-on development experience with Python, including data processing, automation, integrations, and cloud-based applications.

Strong hands-on experience developing and maintaining data solutions using AWS.

Experience with AWS data services such as AWS Glue, Amazon S3, Amazon Redshift, Iceberg, airflow and AWS Lambda.

Strong SQL skills, including query development, optimization, and data manipulation.

Solid experience designing, developing, and maintaining ETL/ELT processes and scalable data pipelines.

Experience integrating multiple data sources and developing reliable data transformation workflows.

Understanding of Data Warehousing, Data Lakes, data modeling, and modern cloud data architecture concepts.

Experience with data quality, monitoring, troubleshooting, and production support.

Experience working in Agile development environments and distributed/global teams.

Advanced English proficiency for daily communication and technical discussions with U.S.-based teams.

Previous experience in Financial Services, Banking, Wealth Management, Asset Management, Capital Markets, Investment Management, or FinTech is highly desirable.

Experience with Apache Spark/PySpark, Amazon Athena, Amazon EMR, Apache Airflow, Kafka, Terraform, Docker, Kubernetes, and CI/CD is considered a plus.

AWS and Data Engineering certifications are desirable.

Main Activities and Responsibilities

Design, develop, enhance, and maintain scalable Python and AWS-based data solutions.

Develop Python applications and components for data processing, automation, transformation, and integration.

Design, build, and maintain scalable ETL/ELT pipelines using AWS technologies.

Develop and maintain data ingestion, transformation, and delivery processes.

Work with services such as AWS Glue, Amazon S3, Amazon Redshift, and AWS Lambda to support cloud-based data solutions.

Develop, optimize, and maintain SQL queries, data models, schemas, and data-processing workflows.

Integrate data from multiple internal and external sources.

Monitor and troubleshoot data pipelines to ensure reliability, performance, integrity, and data quality.

Identify and resolve production issues related to data processing and cloud-based solutions.

Collaborate with Data Engineers, Software Engineers, Architects, Analysts, and business stakeholders to translate requirements into scalable technical solutions.

Participate in code reviews, architecture reviews, technical design discussions, testing, and continuous improvement initiatives.

Support data quality, security, governance, monitoring, and operational excellence practices.

Create and maintain technical documentation, data flows, and development standards.

Support both the development of new solutions and maintenance/enhancement of existing technology systems.

Contribute to the modernization and continuous evolution of the client's AWS-based technology and data ecosystem supporting Wealth & Asset Management business functions.