Join Amazon Web Services (AWS) as a Data Engineer and shape the future of cloud computing. This role is for individuals passionate about data and code, thriving in a fast-paced growth environment. You'll tackle massive datasets, building robust data engineering solutions that process millions of records. Become a key contributor to the AWS supply chain Finance (SCF) organization, working with a dynamic team on scalable, secure, and impactful data infrastructure.

The IFBIT team is dedicated to simplifying and automating processes, fostering data-led decision-making, and delivering crucial insights for improved financial and business performance. We champion innovation and collaboration, developing scalable products that reduce manual efforts, boost efficiency, and strengthen controllership, ultimately enhancing AWS financial performance sustainably.

Design and implement large-scale data pipelines and ETL processes utilizing AWS technologies.

Lead the design of complex data architectures, ensuring they are scalable, secure, and aligned with business objectives.

Develop and maintain efficient, scalable data pipelines and curated datasets for AI consumption and self-service analytics.

Proactively identify and resolve system-wide data challenges, including performance bottlenecks and architectural issues.

Optimize application and query performance using profiling tools and advanced SQL techniques.

Analyze and solve problems at their core, understanding the broader context of issues.

Stay current with emerging data technologies and conduct pilot studies to design data architectures capable of handling increasing data volumes with AWS.

Continuously enhance ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.

Navigate ambiguous situations, making informed decisions using both quantitative analysis and business judgment.

Adopt and promote best practices in data integrity, test design, analysis, validation, and documentation.

Ensure data solutions are auditable, accessible, and maintainable across the organization.

Collaborate with cross-functional teams to deliver innovative data solutions.

A minimum of 5 years of dedicated data engineering experience.

Proven experience in data modeling, warehousing, and constructing ETL pipelines.

At least 5 years of hands-on SQL experience.

Proficiency in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.

Demonstrated experience as a data engineer or in a related specialty (e.g., software engineer, business intelligence engineer, data scientist), with a strong track record of manipulating, processing, and deriving value from large datasets.

A Bachelor's degree or its foreign equivalent in computer science, engineering, analytics, mathematics, statistics, IT, or a related field is required.