Business Intelligence Engineering Lead, Marketing Decision Science
(Menlo Park, CA)
Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started.
The Marketing team focuses on building Facebook brand presence, improving user sentiment and product education. It is an exciting time at Facebook Marketing because understanding people and connecting them to Facebook and our products (and vice versa) is crucial for future growth. We are seeking a talented Business Intelligence Engineering Lead who thrives at the intersection of data science, marketing, product, and engineering. In this role, you will focus on finding ways to scale the analytics function by building the data infrastructure and reporting that informs our marketing efforts, and leveraging these tools to develop insights and drive impact. You will engage with some of the brightest minds in the industry, work with one of the richest data sets in the world, use innovative technology, and see your efforts effect products and people on a regular basis. You will do so by partnering with cross-functional teams and internal stakeholders, and building scalable solutions that provide business critical insights and metrics, while ensuring the best uptime and responsiveness.The idea candidate will be a scrappy self-starter, focused on results, and have a strong technical and analytical background – with a hunger to make significant business impact by owning and driving business decisions and outcomes. Strong time management and communication skills are critical, and a passion for Facebook is necessary. This is a full-time position based in our office in Menlo Park.
- Design, build and launch efficient & reliable data pipelines, systems, and tools to enable faster consumption and understanding of data.
- Partner with marketing, decision science, research and product organizations to understand analytic needs, and build efficient and scalable data solutions that support our marketing efforts.
- Develop ETL processes, ad hoc reports, and models to support marketing decision-making. Analysis areas might include (but not limited to): retention, lifetime value, messaging, promotions, usage, and engagement.
- Build data expertise and own data quality for the Marketing organization.
- Manage the delivery of high impact dashboards, reports, and data visualizations that track key metrics and performance trends, and provide actionable insights to marketing leadership.
- Work across multiple teams in high visibility roles and own the solution end-to-end.
- 5+ years of experience in data analysis.
- 4+ years experience with SQL (Oracle, Vertica, Hive, etc.) and object-oriented programming languages.
- 4+ years experience with Tableau or other visualization tools.
- 3+ years experience with data warehousing, schema design, dimensional data modeling.
- 3+ years experience in custom ETL design, implementation and maintenance.
- BA/BS in Computer Science, Statistics, Math, Physics, or other technical field.
- Communication skills, including the ability to identify and communicate data-driven insights.
- Ability and interest in managing and communicating data warehouse and marketing infrastructure plans to internal clients.
- Experience using SPSS, SAS, R, Python, Matlab, or similar statistical packages.
- Statistical and data analysis/modeling skills (e.g. significance testing, regression modeling, etc.)
- PHP and web design experience.
- An advanced degree in computer science, statistics, economics, behavioral or social science, or a related quantitative field.
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