Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.
Responsibilities
Proactively drive the vision for Business Intelligence (BI) and Data Warehousing across a product vertical, and define and execute on a plan to achieve that vision. Define the processes needed to achieve operational excellence in all areas, including project management and system reliability. Build a high quality BI and Data Warehousing team and design the team to scale. Build cross-functional relationships with Data Scientists, Product Managers and Software Engineers to understand data needs and deliver on those needs. Manage data warehouse plans across a product vertical. Drive the design, building, and launching of new data models and data pipelines in production. Manage development of data resources and support new product launches. Drive data quality across the product vertical and related business areas. Manage the delivery of high impact dashboards and data visualizations. Define and manage SLA’s for all data sets and processes running in production.
Qualifications
Requires a Bachelor’s degree (or foreign equivalent) in Electronic Engineering, Computer Science, Computer Software, Engineering, Applied Sciences, Mathematics, Physics, or related field, followed by six years of progressive, post-baccalaureate work experience in the job offered or in a computer-related occupation Requires six years of experience in the following: Data ETL (Extract, Transform, Load) design, implementation, and maintenance on a large scale Programming in Python, Perl, Java, Javascript, or PHP Writing SQL statements Analyzing large volumes of data to identify deliverables or to provide data driven insights, gaps, and inconsistencies Data warehousing architecture and plans Informatica, Talend, Pentaho, dimensional data modeling, or schema design Hadoop, HBase, or Hive