Data Engineer, Technical Leadership (Ranking, AI)

Ranking AI is the central core machine learning org within Meta’s Monetization group, powering Meta’s revenue and business growth by advancing and deploying state-of-the-art Recommendation Systems AI for our Ads stack. We are currently redesigning the large and fragmented ads model space by developing new modeling architectures, advancing the scale limit through model-hardware co-design, and developing techniques that better leverage anonymized, aggregated data. While there is significant focus on innovation, we pride ourselves in being able to translate research to production with high velocity, delivering on half-over-half revenue targets in a predictable fashion

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 experience a direct correlation between your work, company growth, and user satisfaction. You’ll collaborate with experienced engineers, researchers, and cross-functional partners, work with large-scale, diverse data sets, use modern technology, and see your efforts affect products and people on a regular basis.

Move to MINIMUM_QUALIFICATION or PREFERRED_QUALIFICATIONS.

Responsibilities

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

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 authoring SQL statements Experience analyzing data to identify deliverables, gaps and inconsistencies Experience managing and communicating data warehouse plans to cross-functional stakeholders Experience driving projects independently within distributed, global teams Experience working with either a MapReduce or an MPP system Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience influencing product decisions with data Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) BS/BA in Technical Field, Computer Science or Mathematics Knowledge and practical application of Python