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Revenue Platforms Data Engineer

Google is a global technology company that specializes in internet-related services and products, including search, cloud computing, software, and hardware.
Data
Mid-Level Software Engineer
3+ years of experience
AI · Finance
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Job Description

In this role your mission is to simplify and centralize the prioritization and deployment of smart, Quote-to-Report (Q2R) digitalization to deliver the highest Return on Investment (ROI) on Finance platforms, for Alphabet. Ultimately, we aim to enable Q2R systems, processes and data fit for Finance that allow every product, anywhere, anytime, the right way, effortlessly.

Responsibilities: • Collaborate with Stakeholders: Work with finance Subject matter experts to understand report requirements and provide necessary data solutions, access and support. • Develop and Maintain Data Pipelines: Design and implement Extract, Transform, and Load (ETL) processes (SQL, Python) to ensure timely and accurate collection and integration of financial data from various sources. • Manage Data Architecture: Understand internal infrastructure to select appropriate sources and technologies to manage data, and design data architecture to support financial reporting. Ensure data security and compliance. • Ensure Data Quality: Implement data validation and cleansing processes to maintain quality data for accurate revenue reporting. • Automate manual tasks and design scalable data solutions. Efficiently handle volumes of financial data.

At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google's technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.

Last updated a year ago

Responsibilities For Revenue Platforms Data Engineer

  • Collaborate with Stakeholders to understand report requirements and provide necessary data solutions, access and support
  • Develop and Maintain Data Pipelines: design and implement ETL processes (SQL, Python) for financial data
  • Manage Data Architecture: understand internal infrastructure, select appropriate sources and technologies, design data architecture for financial reporting
  • Ensure Data Quality: implement data validation and cleansing processes
  • Automate manual tasks and design scalable data solutions

Requirements For Revenue Platforms Data Engineer

Python
  • Bachelor's degree in Business, Finance, a related quantitative field, or equivalent practical experience
  • 3 years of experience with Finance systems, accounting, operations, tax, internal controls, requirements documentation, testing, and validation
  • Experience of SQL/database management
  • Experience of Object-Oriented Programming