Every month, billions of people leverage Meta products to connect with friends and loved ones from across the world. On the Data Engineering Team, our mission is to support these products both internally and externally by delivering the best data foundation that drives impact through informed decision making. As a highly collaborative organization, our data engineers work cross-functionally with software engineering, data science, and product management to optimize growth, strategy, and experience for our 3 billion plus users, as well as our internal employee community.We are looking for a technical leader in our Data Engineering team to work closely with Product Managers, Data Scientists and Software Engineers to support building out a great platform for the future of computing. In this role, you will see a direct correlation 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.The ideal candidate will have strong data infrastructure and data architecture skills as well as experience in areas such as governing company wide data marts, enabling security and privacy data solutions, and full stack experience with analytical technologies. Candidates should also have a proven track record of leading and scaling efforts related to end-to-end analytics systems, strong operational skills to drive efficiency and speed, strong project management leadership, and a strong vision for how data can proactively improve companies.As we continue to expand and create, we have a lot of exciting work ahead of us!

MINIMUM QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 10+ years experience in the data warehouse space.
• 10+ years experience in custom ETL design, implementation and maintenance.
• 10+ years experience with object-oriented programming languages.
• 10+ years experience with schema design and dimensional data modeling.
• 10+ years experience in writing SQL statements.
• Experience analyzing data to identify deliverables, gaps and inconsistencies.
• Experience managing and communicating data warehouse plans to internal clients.

PREFERRED QUALIFICATIONS:

• BS/BA in Technical Field, Computer Science or Mathematics.
• Experience working with either a MapReduce or an MPP system.
• Knowledge and practical application of Python.
• Experience working autonomously in global teams.
• Experience influencing product decisions with data.

• Proactively drive the vision for data foundation and analytics to accelerate building and improvement of cross platform components across Instagram, and define and execute on plan to achieve that vision.
• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems.
• Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve.
• Build cross-functional relationships with Data Scientists, Product Managers and Software Engineers to understand data needs and deliver on those needs.
• Define and manage SLA for all data sets in allocated areas of ownership.
• Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership.
• Design, build, and launch collections of sophisticated data models and visualizations that support use cases across different products or domains.
• Solve our most challenging data integrations problems, utilizing optimal ETL patterns, frameworks, query techniques, sourcing from structured and unstructured data sources.
• Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts.
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.
• Influence product and cross-functional teams to identify data opportunities to drive impact.
• Mentor team members by giving/receiving actionable feedback.