Job
Description
As a Senior Data Analyst at our company, you will play a crucial role in driving strategic decisions and shaping the future of our Product/Operations team. Your primary responsibilities will include: - **Advanced Data Analysis**: Utilize advanced SQL skills to query, analyze, and manipulate large, complex datasets. Develop and maintain robust, scalable dashboards and reports to monitor key performance indicators (KPIs). - **Source Code Management**: Effectively manage, version, and collaborate on code using codebase management systems like GitHub. Uphold data integrity, produce reproducible analyses, and foster a collaborative database management environment through best practices in version control and code documentation. - **Strategic Insights**: Partner with product managers and business stakeholders to define and answer critical business questions. Conduct deep-dive analyses to identify trends, opportunities, and root causes of performance changes. - **Data Architecture & Management**: Work closely with data engineers to design, maintain, and optimize data schemas and pipelines. Provide guidance on data modeling best practices and ensure data integrity and quality. - **Reporting & Communication**: Translate complex data findings into clear, concise, and compelling narratives for both technical and non-technical audiences. Present insights and recommendations to senior leadership to influence strategic decision-making. - **Project Leadership**: Lead analytical projects from end to end, including defining project scope, methodology, and deliverables. Mentor junior analysts, fostering a culture of curiosity and data-driven problem-solving. **Qualifications Required**: - Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or a related discipline. - 5+ years of professional experience in a data analysis or business intelligence role. - Expert-level proficiency in SQL with a proven ability to write complex queries, perform window functions, and optimize queries for performance on massive datasets. - Strong understanding of data architecture, including data warehousing, data modeling (e.g., star/snowflake schemas), and ETL/ELT principles. - Excellent communication and interpersonal skills, with a track record of successfully influencing stakeholders. - Experience with a business intelligence tool such as Tableau, Looker, or Power BI to create dashboards and visualizations. - Experience with internal Google/Alphabet data tools and infrastructure, such as BigQuery, Dremel, or Google-internal data portals. - Experience with statistical analysis, A/B testing, and experimental design. - Familiarity with machine learning concepts and their application in a business context. - A strong sense of curiosity and a passion for finding and communicating insights from data. - Proficiency with scripting languages for data analysis (e.g., App scripting, Python or R) would be an added advantage.,