Data Engineer, Product Analytics

Meta - Burlingame, CA

Full-time - Mid Level

Burlingame, CA

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About the position

The Data Engineer, Product Analytics at Meta plays a crucial role in optimizing growth, strategy, and user experience for over 3 billion users. This position involves collaborating with cross-functional teams to tackle complex data challenges, ensuring data integrity, and contributing to the overall success of the company through effective data architecture and management.

Responsibilities

• Conceptualize and own the data architecture for multiple large-scale projects, evaluating design and operational cost-benefit tradeoffs.
• Create and contribute to frameworks that improve the efficacy of logging data, while resolving issues with data infrastructure.
• Collaborate with engineers, product managers, and data scientists to understand data needs and represent key insights meaningfully.
• Define and manage SLA for all data sets in allocated areas of ownership.
• Implement security models based on privacy requirements and address data quality issues.
• Design, build, and launch sophisticated data models and visualizations for various products or domains.
• Solve challenging data integration problems using optimal ETL patterns and frameworks.
• Optimize existing processes running in production and complex code through advanced algorithmic concepts.
• Optimize pipelines, dashboards, frameworks, and systems for easier development of data artifacts.
• Influence product and cross-functional teams to identify data opportunities that drive impact.
• Mentor team members by providing and receiving actionable feedback.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
• 4+ years of work experience in data engineering (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).

Nice-to-haves

• Master's or Ph.D degree in a STEM field.
• Experience with data processing automation, data quality, data warehousing, data governance, business intelligence, data visualization, and data privacy.
• Experience working with terabyte to petabyte scale data.

Benefits

• Competitive salary and performance bonuses.
• Health insurance and wellness programs.
• Flexible scheduling and remote work options.
• Professional development opportunities and continued education support.