Amazon

Data Engineer, Ops Finance Transportation

Posted On

May 6, 2024

Location

Hyderabad, Telangana

Experience Level

Freshers/Experienced

Job Type

Finance & Accounting

Apply By

July 2, 2024

Job Description

The Amazon transportation controllership team is looking for a Data Engineer who is data-driven and detail oriented, to partner in expanding our financial data systems to support our global transportation network. You should have excellent business and communication skills to be able to work with business owners and tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate. This person must be strategic and have strong analytical skills, robust interpersonal and influencing skills, strong organizational and project management skills, and is a self-starter.

Key job responsibilities
- Develop end to end scalable data infrastructure and data pipelines
- Develop data products, deploy highly performant solutions, build data infrastructure leveraging AWS services (such as EC2, Redshift, EMR, Lambda, Quicksight etc.)
- Improve existing solutions and recommend data architecture to improve scale, quality, timeliness, coverage, monitoring and security.
- Develop new data models and end to data pipelines.
- Lead design reviews for other Data Engineers on the team and actively participate in design reviews of related tech products.
- Provide technical and thought leadership for Data Engineering and Business Intelligence
- Create and implement Data Governance strategy for mitigating privacy and security risks
- Design, implement, and support a platform providing secured access to large datasets.
- Interface with auditing and controllership customers, gathering requirements and delivering complete data solutions.
- Develop ETL pipeline that links various datasets that could serve the analysis objectives in the most efficient way
- Analyze and solve problems at their root, stepping back to understand the broader context.

A day in the life
Work with the largest dataset in logistics management in the world to drive business insights, support operations and build analytical solutions for partners which can help drive cost control and decision making. As a Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments. You will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models, Gen Ai and ad-hoc data requests. You will be exposed to cutting edge AWS big data technologies.

About the team
Trans Controllership in Finance is one of the most challenging and exciting spaces to work for, with new geographies, new modes and new carriers being launched every day and being required to seamlessly integrate with the Transportation technical systems for automatic Ingestion of Freight invoices, thorough auditing, timely payment and for proper accounting to keep our books clean and accurate.

We are open to hiring candidates to work out of one of the following locations:

Hyderabad, TS, IND- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Design & Implementation of automated data contract and data quality enforcement mechanisms
- Expertise at least in 1 data Orchestration tool
- Working experience in CDK
- Experience in discovering business requirements and creating insightful dashboards tailored for various levels of the organization, including senior leadership.
- The successful candidate will be able to deliver products that exceed customer satisfaction, ensure data accuracy and completeness, automate manual tasks and develop efficient data pipelines.

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