Revenue Platforms Data Engineer
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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.
Minimum qualifications:
- 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.
Preferred qualifications:
- Experience in collaborative coding and version control.
- Experience in machine learning, including data preparation, model selection, performance evaluation, and parameter tuning.
- Ability to maintain professional and influential presence with excellent communication and customer service skills.
- Ability to drive operational process improvements.
- Passion for developing and analyzing complex data sets and converting them into actionable business insights.
About the job
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 understands 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 implements 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.
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