Big Data Engineer, Global Finance Technology (GFT)

Job Description

Are you an experienced Big Data Engineer passionate about building scalable and enterprise-level data engineering solutions? This opportunity is a great fit for an experienced Big Data Engineer who enjoys working on large-scale computing leveraging AWS distributed systems. In addition to technical expertise, you will invest time to understand the needs of the business, the data behind it, and how to transform information into technical solutions that allow the business to take action.
Key job responsibilities
– Design and build scalable big data pipelines to ingest, transform and publish massive amounts of data at scale
– Troubleshoot system and data quality issues
– Identify bottlenecks with current architecture and propose efficient and long term solutions
– Provide operational support by participating in team’s on call rotations
– Mentor junior engineers with respect to development and design standards
– Lead projects from initial design through to full implementation
A day in the life
As a data engineering team that supports the central finance team within Amazon, our primary customer will always be our CFO. Hence a day to day activity of a big data engineer within this team will mostly revolve around solving data engineering problems for transforming our ever growing financial data. You work with other financial teams to understand their business problems and deliver scalable technical solutions.
About the team
GFT Data Services team is the data engineering team within Corp FP&A. On our team, we enjoy a unique vantage point into everything happening within Amazon. As part of that, this role would be part of a team that is responsible for Company’s enterprise-wide financial planning & analytics environment. The data flowing through our platform directly contributes to decision-making by our CFO and all levels of finance leadership. If you’re passionate about building tools that enhance productivity, improve financial accuracy, reduce waste, and improve work-life harmony for a large and rapidly growing finance user base, come join us!

BASIC QUALIFICATIONS

– 3+ years of data engineering experience
– Experience with data modeling, warehousing and building ETL pipelines
– Experience with SQL

PREFERRED QUALIFICATIONS

– Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
– Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)