Drimva

Meta

Data Engineer, Meta Superintelligence Labs (Mobile Client)

$177K–$247K

Bellevue, WA +2 · Full-time · Posted Sep 14, 2026

Location
Bellevue, WA
Menlo Park, CA
New York, NY
Experience
7+ years of data-focused experience; 7+ years with SQL, ETL, data modeling, and at least one programming language.
Education
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

About the job

Owns mobile client logging and measurement for an iOS and Android consumer application, building instrumentation, data pipelines, and metrics to support product decisions at scale.

What you'll do

  • Design, implement, test, and maintain client-side product and performance instrumentation in production iOS and Android codebases; establish logging standards and automated validation.
  • Build and operate scalable data architecture, pipelines, models, and visualizations, ensuring data quality, security, and service-level agreements.
  • Partner with product, engineering, and data science teams to define measurement, identify data opportunities, and scale instrumentation practices.

What they ask for

  • Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
  • 7+ years of experience in roles primarily involving data.
  • 7+ years of experience with SQL, ETL, data modeling, and at least one programming language.
  • Hands-on experience implementing, debugging, and validating client-side logging and instrumentation in production iOS and Android codebases, including authoring and landing the instrumentation code.

Nice to have

  • Master's or Ph.D degree in a STEM field.
  • Demonstrated experience prioritizing instrumentation and measurement investments on fast-moving consumer surfaces with constrained engineering capacity, and establishing standards across teams and platforms.

Pay

USD $177,000/year to $247,000/year (base salary)

Tools

iOS, Android, SQL, ETL, Python, C++, C#, Scala

AI focus

Use AI tools to optimize or redesign workflows and drive measurable impact; follow responsible AI practices, and develop skills in prompt/context engineering and agent orchestration.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 4, 2026 (UTC)