Data Engineering Manager, Analytics

Do you want to use data to help drive the direction of products that impact the lives of over 1 billion people every day? If yes, we want to talk to you. We're looking for a leader in our Data Engineering team to work closely with Product Managers, Data Scientists and Software Engineers to support product launches and roadmaps by building the data architecture that informs and drives insight. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with some of the brightest minds in the industry, work with one of the richest data sets in the world, use cutting edge technology, and see your efforts affect products and people on a regular basis.

10. 8+ years of experience in BI and Data Warehousing.
11. Experience scaling and managing 3+ person teams.
12. Communication and leadership experience, with experience initiating and driving projects.
13. Project management experience.
14. Data architecture experience.
15. Experience in SQL or similar languages.
16. Development experience in at least one object-oriented language (Python, Java, etc.).
17. BA/BS in Computer Science, Math, Physics, or other technical fields.

Preferred Qualifications:

Preferred Qualifications:
18. Experience in a consumer web or mobile company.
19. Experience with data sets, Hadoop, and data visualization tools.
20. Advanced degree

1. Proactively drive the vision for BI and Data Warehousing across a product vertical, and define and execute on a plan to achieve that vision.
2. Define the processes needed to achieve operational excellence in all areas, including project management and system reliability.
3. Build a high-quality BI and Data Warehousing team and design the team to scale.
4. Build cross-functional relationships with Data Scientists, Product Managers and Software Engineers to understand data needs and deliver on those needs.
5. Manage data warehouse plans across a product vertical.
6. Drive the design, building, and launching of new data models and data pipelines in production.
7. Drive data quality across the product vertical and related business areas.
8. Manage the delivery of high impact dashboards and data visualizations.
9. Define and manage SLA's for all data sets and processes running in production.