The Finance Operations and Analytics team sits at the intersection of our core data engineering teams, Finance, and Business Operations teams to enable high impact business analytics. As a member, you’ll focus on implementing scalable systems and processes that provide metrics visibility for our senior leaders, enable business analysts to generate insights, and power our mission-critical reporting as a public company.

The successful candidate will have experience working with enterprise data warehouses, be passionate about empowering people to make data driven decisions, and be excited to liberate data through fast scalable datasets. Additionally, you will also be the product owner, project manager and technical lead for your data area. 

What you’ll do:

• Define product/project requirements with business stakeholders and establish effective project governance structure to make progress on your initiatives
• Build scalable data assets (dashboards, underlying data models, and workflows) to unlock reliable and high velocity decision support that our customers provide to the rest of Pinterest
• Enable & educate business analysts on best practices for leveraging new data assets that you create
• Collaborate with both central technical teams and business stakeholders on both roadmap planning and project execution, bridging the gap between business problem and technical solution
• Bring engineering rigor to various analytics initiatives by building scalable solutions and following SDLC best practices
• Navigate bottlenecks, scales for efficiency, and optimizes for clarity for the team; proactively unblocks roadblocks on cross-functional coordination and org alignment issues Defines project scope for complex issues

What we’re looking for:

• Hands-on experience in principled data warehouse design, data visualization and data pipeline design and development
• 7+ years of hands-on experience with data platforms (Hadoop, Hive, Presto, Spark and Snowflake ) and with data visualization (Tableau) technologies
• Expert-level proficiency in writing complex, highly-optimized SQL queries across large datasets
• Working knowledge of Airflow and associated python data libraries (Pandas, NumPy, Matplotlib, etc.)

This position is not eligible for relocation assistance.

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