Data Engineer, Teen & Family Experience (TFE)
Immigration summary
Visa sponsorship
This employer sponsors this kind of work repeatedly, and is still filing this year.
5,686 recent H-1B filings · 246 similar-role filings
View visa evidenceGreen card sponsorship
This employer has recently sponsored green cards at scale.
742 recent certified PERM filings · 119 similar-role filings
View green card evidenceJob description
As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide. Teen & Family Experience is a shared, cross-functional team within Meta's Central Youth org, sitting under the Teen and Family Experiences pillar. Its mission is to equip teens to have safe and supportive experiences across Meta technologies, and to provide centralized services and support so app partners across the Family of Apps can efficiently ship youth-experience improvements and meet youth compliance obligations. You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond. Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a strong focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems. Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities. Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Responsibilities
- Scope significantly expands the parental-controls and teen-experience surface needing measurement.
- The expanded surface is concrete and teen-facing: productive pauses, the non-personalized feed option, nighttime mode, and school mode.;.
- Measurement for a large slate of parental-controls and teen-experience features, both new and newly enhanced.;.
- Accountable end to end for each metric: logging, staging data, aggregate datasets, the pipeline work behind them, and the dashboards that surface the result.;.
- The split of that work varies by metric.
- On some, Instagram or Facebook handle the logging and staging and this person builds the metrics and dashboards; on others this person does the logging and hands off.
- Deciding who takes which piece — based on availability, technical skills across teams, and domain knowledge — is part of the role.
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 4+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions
- 4+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)
Preferred Qualifications
- Master's or Ph.D degree in a STEM field
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Sponsorship evidence
Why Openbound reached the conclusions above.
Visa sponsorship evidence
Current posting
Silent on sponsorship
Employer H-1B history
- 5,686
- recent certified H-1B filings
- 3,007
- new-hire petitions
- 246
- filings for similar roles
- 5,150
- so far in FY2026
Filed titles like this role: data engineer · data developer · data engineer bp and t
More evidence details
- 246 certified H-1B filings for this same role, 3,007 new-hire petitions across the employer, and 2,752 new hires already this year
- 246 certified H-1B filings for this same role
- 5,686 recent certified H-1B filings across the employer
- Still filing this year — 5,150 filings in FY2026
- 2,778 USCIS H-1B new-employment approvals, counted separately from LCA filings
- Strong filing activity in CA
- 11,582 further USCIS approvals for extensions or transfers
- The posting says nothing about sponsorship either way
Strong filing activity in CA.
Green card sponsorship evidence
Employer PERM history
- 742
- recent certified PERM filings
- 119
- filings for similar roles
- 478
- filings in this location
Filing history reflects past employer behavior; it isn't a promise for this opening.
All open roles at MetaHow Openbound evaluates sponsorship
Visa history uses official U.S. Department of Labor H-1B LCA disclosure data and USCIS H-1B petition history. Green card history uses DOL PERM disclosure data. Each is read for the employer as a whole, for roles like this one, and for this location, weighted toward the most recent fiscal years.
An employer is matched to its filing entities by verified legal name and reviewed aliases; a match is never made on a name resemblance alone. Where no verified entity can be matched, the page says so and draws no conclusion from the absence. 1,277 filing titles were examined for this employer.
What this posting states outranks history in both directions, and an employer's published policy outranks past filings. Filing history reflects past behavior; it is not a promise of sponsorship for this opening, and none of this is legal advice.