Data Engineer, Product Analytics - Sunnyvale, CA | Los Angeles, CA | Bellevue, WA | Redmond, WA | Menlo Park, CA | Seattle, WA | Burlingame, CA | Washington, DC | New York, NY | San Francisco, CA | Remote, US
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
- Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems
- Identify the data needed for a business problem and implement logging required to ensure availability of 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
- Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership
- Design, build and launch new data models and visualizations in production, leveraging common development toolkits
- Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around efficient queries
- Support existing processes running in production and implement optimized solutions with limited guidance
- Define and manage SLA for data sets in allocated areas of ownership
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- 2+ years of work experience in data engineering
- Experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)
- 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/PerksBenefits Bonus Equity Other benefits provided by Meta
SkillsAutomation C C++ Computer Science Data Modeling Data processing Data Visualization Data Warehousing ETL Modeling Organization Product Management Python Scala Software Engineering SQL Technical
Tasks- Build data expertise and leverage data controls
- Collaborate with cross functional teams
- Define and manage SLA for data sets
- Design, build, and launch new data extraction, transformation, and loading processes
- Design, build, and launch new data models and visualizations
- Identify data needed for business problems
- Manage and execute data warehouse plans
- Manage SLA for data sets
- Support existing processes and implement optimized solutions
2+ years
EducationAnalytics Bachelor's degree Bachelor's degree in Computer Science Computer Engineering Computer Science Engineering Equivalent practical experience Physics Relevant technical field
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-4 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9