Data Engineer, Technical Leadership (Ranking, AI

Position: 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  or .Data Engineer, Technical Leadership (Ranking, AI) 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

Minimum Qualifications:

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

Preferred Qualifications:

Experience driving projects independently within distributed, global teams

Experience working with either a Map Reduce 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…