Design and optimize data pipelines and ETL processes to support analytics and BI initiatives. Collaborate with teams to deliver modern cloud-based solutions.
Responsibilities
In this position, you will design, develop, and optimize complex data pipelines and systems to support analytics and business intelligence initiatives. This is an exciting opportunity to work within a collaborative team and gain exposure to modern cloud technologies in the asset management industry. Responsibilities include designing and developing scalable data pipelines and ETL processes, building and maintaining data models and analytics infrastructure, collaborating with data analysts and business stakeholders, leading technology modernization initiatives including cloud migration, optimizing data systems for performance and security, and ensuring compliance with data governance standards.
Requirements
5+ years of experience in Data Engineering, ETL development, and data architecture. Strong proficiency in Python and SQL for data processing and automation. Solid understanding of data modeling, data warehousing, and analytics concepts. Experience with AWS data services such as SageMaker, AWS Unified Studio, or comparable tools. Proven track record of leading modernization and migration projects. Excellent problem-solving, communication, and teamwork skills. Nice to have: Experience with SAS and WebFOCUS, exposure to machine learning workflows on AWS, knowledge of data governance and compliance, familiarity with CI/CD pipelines for data engineering, hands-on experience with cloud-based data platforms (particularly AWS), and prior experience in banking or financial services.
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