Data Engineer, Product Analytics - Sunnyvale, CA | Remote, US | Bellevue, WA | Redmond, WA | Austin, TX | Menlo Park, CA | Seattle, WA | Burlingame, CA | Washington, DC | New York, NY | Fremont, CA
As a highly collaborative organization, our data engineers work cross-functionally with software engineering, data science, and product management to optimize growth, strategy, and experience for our 3 billion plus users, as well as our internal employee community. In this role, you will see a direct correlation between your work, company growth, and user satisfaction. Beyond this, you will work with some of the brightest minds in the industry, and you'll have a unique opportunity to solve some of the most interesting data challenges with efficiency and integrity, at a scale few companies can match.Data Engineer, Product Analytics Responsibilities
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta. Apply
- 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
- Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
- 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 multiple use cases across different products or domains
- Solve our most challenging data integration 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
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- 4+ years of work experience in data engineering (a minimum of 2+ years with a Ph.D)
- Experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)
- Master's or Ph.D degree in a STEM field
- Experience with one or more of the following: data processing automation, data quality, data warehousing, data governance, business intelligence, data visualization, data privacy
- Experience working with terabyte to petabyte scale data
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta. Apply
Job Profile
Regions Countries Benefits/Perks SkillsArchitecture Automation C C++ Computer Science Data Architecture Data Infrastructure Data Modeling Data processing Data Visualization Data Warehousing ETL Modeling Organization Product Management Python Recruiting Scala Software Engineering SQL Technical
Tasks- Collaborate with cross functional teams
- Contribute to frameworks for logging data
- Define and manage SLA for data sets
- Design and launch data models and visualizations
- Identify data opportunities
- Implement security model based on privacy requirements
- Influence product teams to identify data opportunities
- Mentor team members
- Optimize data integration problems
- Optimize pipelines and systems
- Own data architecture for large-scale projects
- Work cross-functionally
4+ years
EducationAnalytics Bachelor's degree Bachelor's degree in Computer Science Computer Engineering Computer Science Engineering Equivalent practical experience Master's or Ph.D degree in a STEM field Physics Relevant technical field STEM field
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9