Data Engineer, Revenue Platforms

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 3 years of experience coding with one or more programming languages (e.g., Python, Java, C/C++).
• 3 years of experience designing data pipelines (ETL) and model data, for synch and asynch system integration and implementation.
• 3 years of experience analyzing data, database query (e.g., SQL), and creating dashboards/reports.

Preferred qualifications:

• Master’s degree in Engineering or Computer Science or a related field, or equivalent practical experience.
• 3 years of experience partnering and managing stakeholders (e.g., users, partners, customer).
• Experience with JavaScript and web applications, including front-end frameworks (e.g., Angular, React, Polymer) or backend web services and microservices on cloud infrastructure.
• Familiarity with core web technologies (e.g., HTTP, TCP/IP, HTML, CSS, XML).
• Knowledge of machine learning, including data preparation, model selection, performance evaluation, and parameter tuning.
• Passion for developing/analyzing complex data sets and converting them into business insights.

About the job

The Business Platforms team's mission is to drive digitalization across Alphabet's Quote to Report (Q2R) processes, to enable business for every product, anywhere, seamlessly and in the right way.

The team works at the intersection between Financial Reporting business processes and the systems that support them. We understand the multiple business models and products that Alphabet offers in depth. We articulate the business processes required to support them and engage in the design and deployment of digitalization solutions in collaboration with Engineering partners.

System optimization and tooling, automation, data management, and systems infrastructure architecture and support are just a few of the items that we cover. The range of digitalization solutions that we manage evolves constantly, in tandem with the direction of the business and the requirements to enable business.

The Business Platforms Data Engineer will be focused on understanding our business systems and code base to execute on internal and external reporting requests, as well as implementing opportunities to optimize our reporting data infrastructure.

In this role, you will partner with our Controllership, Tax, External Reporting, Data Governance, and Legal teams to understand business requirements and collaborate with Engineering stakeholders to provide timely data to manage financial risk and adhere to regulatory requirements. You will also be responsible for developing scalable data pipelines and automations. You will have attention to detail with a proven ability to work well with other teams, provide outstanding customer service, deliver on deadlines, and produce flawless work.

The US base salary range for this full-time position is $124,000-$178,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Collaborate cross-functionally to design and maintain data pipelines and systems. Partner with internal teams to implement data solutions that improve Finance and reporting processes.
• Analyze data critically, identify gaps, and architect data solutions to automate business reporting.
• Utilize programming languages (e.g., SQL, PLX, Python) to produce readable, well-structured code, and develop and maintain data models and pipelines to support data visualization, analysis, and reporting.
• Maintain the highest development practices, including technical design, solution development, testing, and issue resolution.
• Cultivate understanding of Google’s Infrastructure, data structures, and their relationship and impact on financial business processes.