Data Program Manager, Finance Data and Analytics
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Minimum qualifications:
- Bachelor's degree in a quantitative discipline or equivalent practical experience.
- 4 years of experience in business intelligence, analytics, or quantitative analysis related fields.
- Experience with SQL and scripting in one or more programming languages (e.g., R, Python, JavaScript).
Preferred qualifications:
- Experience working in a development lifecycle, defining requirements, checking in code, testing, staging, production.
- Experience in implementing Analytics and reporting solutions like data warehousing and business intelligence as a program manager or team lead.
- Track record of managing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
- Ability to translate analysis results in business recommendations.
- Ability to define goals, strategy, and roadmaps for data initiatives, while managing stakeholder expectations and aligning cross-functional teams.
- Excellent problem-solving skills, with the ability to analyze complex data sets, gather insights, and develop reporting solutions that support decision making processes.
About the job
At Google, data drives all of our decision-making. As part of the Finance Business Intelligence team, you will use data to inform business and product decisions across the company. Using your technical skills, business acumen and creativity, you will build tools to automate reporting and generate insight that will allow clients to quickly and accurately see how our key business products and processes are performing. Previous experience managing finance systems projects, with emphasis on providing business intelligence and data driven insight through reporting, will have equipped you well for this role. You’ll be involved in projects from inception to delivery, ensuring that your reporting delivers high-quality and relevant data to intelligently grow our business. You will also have extensive knowledge of key financial systems, such as Oracle and Hyperion, and experience working with a range of other business intelligence tools and platforms.
Finance Data and Analytics (DnA) team combines business acumen, technology and innovation to organize data, enable insights and create data driven and efficient Finance organizations in Google. You will have a unique opportunity to gain perspectives on Google’s core businesses, services and the products. At Google, data drives all of our decision-making.
In this role, you will collaborate with data engineers, analysts and BI analysts to create data solutions to enable our finance partners to make informed decisions, manage risks and opportunities. You will develop solutions to high visibility data challenges. You organize data, enable insights and collaborate to create the world’s most data-driven and Finance organization. You will take initiative and ability to grow in environments with multiple cross-functional stakeholders with differing priorities.The name Google came from "googol," a mathematical term for the number 1 followed by 100 zeros. And nobody at Google loves big numbers like the Finance team when providing in depth analysis on all manner of strategic decisions across Google products. From developing forward-thinking analysis to generating management reports to scaling our automated financial processes, the Finance organization is an important partner and advisor to the business.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $124000 - $178000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Partner with Finance teams to understand data needs, building and securing intelligent, high-quality data solutions that provide actionable insights for decision-making.
- Deliver impactful data solutions by incorporating best practices in reporting, dashboards, scorecards, and visualization to fill information gaps.
- Maintain development standards, including technical design, clean code, issue resolution, and strict data security protocols.
- Collaborate with BI analysts and data scientists to design process-improving solutions, while defining clear goal, strategy, and agile roadmaps for data initiatives.
- Manage the project lifecycle by overseeing release schedules, milestones, and stakeholder expectations, while driving cross-functional leadership in a fast-paced environment.
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