Data Engineer, Analytics (Ranking, AI)

Meta; Menlo Park (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta in Menlo Park, CA is seeking a Data Engineer focused on analytics for Ranking and AI, on-site. You will own scalable data architectures, develop robust logging frameworks, and partner with engineers, product managers, and data scientists to capture data needs and translate insights into meaningful dashboards and visualizations across multiple products and domains.

You will help establish data governance and quality controls to drive trust and impact.

Qualifications

• 7+ years of experience with SQL.
• Experience with ETL.
• Experience with data modeling.
• Experience with at least one programming language (Python, C++, C#, Scala) or similar.

Responsibilities

• Own and design scalable data architectures for large-scale initiatives.
• Develop logging data frameworks and collaborate with infra teams.
• Partner with engineers, PMs, and data scientists to translate data needs into visualizations.
• Establish and manage SLAs for data sets within domains.
• Design security models aligned with privacy requirements and governance.
• Create, deploy, and launch data models and visualizations for multiple use cases.
• Address complex data integration with ETL patterns across sources.
• Assist in maintaining production data processes and optimize code performance.
• Refine pipelines, dashboards, frameworks, and systems to accelerate data artifacts.
• Influence cross-functional teams to uncover data opportunities and impact.
• Provide mentorship through actionable feedback.

Skills

SQL

ETL

Data modeling

Python

C++

C#

Scala

Education

Master's or PhD in STEM

Tools

SQL

ETL

Python

C++

C#

Scala

Job description

Data Engineer, Analytics focused on Ranking and AI, based in Menlo Park, CA on site.

Responsibilities

• Own and design scalable data architectures for multiple large-scale initiatives, evaluating design choices and cost-benefit tradeoffs across systems.
• Develop and contribute to logging data frameworks to boost data capture effectiveness, collaborating with infrastructure teams to triage and resolve issues.
• Partner with engineers, product managers, and data scientists to capture data needs and translate insights into meaningful visual representations.
• Establish and manage service level agreements for data sets within assigned domains.
• Design and enforce security models aligned with privacy requirements, validate safeguards, address data quality concerns, and evolve governance processes in owned areas.
• Create, deploy, and launch sophisticated data models and visualizations supporting multiple use cases across products and domains.
• Address complex data integration challenges by applying efficient ETL patterns, frameworks, and queries across structured and unstructured sources.
• Assist in maintaining production data processes, optimizing code performance through advanced algorithmic approaches.
• Refine pipelines, dashboards, frameworks, and systems to streamline development of data artifacts.
• Influence product and cross-functional teams to uncover data opportunities that drive measurable impact.
• Provide mentorship through actionable feedback to teammates and peers.

Requirements

• 7+ years of experience with SQL
• Experience with ETL
• Experience with data modeling
• Experience with at least one programming language such as Python, C++, C#, Scala, or similar

Technologies

• SQL
• ETL
• Python
• C++
• C#
• Scala

Benefits

• Bonus
• Equity
• Benefits

Preferred Qualifications

• Proven ability to integrate AI tools to optimize workflows and deliver measurable impact such as efficiency gains or quality improvements
• Ongoing AI skill development including prompt engineering and agent orchestration, keeping pace with emerging AI technologies
• Experience applying responsible, ethical AI practices, including risk assessment, bias mitigation, and quality reviews
• Master's or PhD in a STEM field with coursework or research in data systems, machine learning, or related areas