Data Engineer, Product Analytics

Meta - Burlingame, CA

Full-time

Burlingame, CA

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About the position

As a Data Engineer in Product Analytics at Meta, you will play a crucial role in shaping the data architecture for various large-scale projects. This position requires a highly collaborative approach, as you will work cross-functionally with software engineering, data science, and product management teams to optimize growth strategies and enhance user experiences for over 3 billion users globally. Your contributions will directly correlate with company growth and user satisfaction, providing a unique opportunity to tackle some of the most interesting data challenges at an unparalleled scale. In this role, you will conceptualize and own the data architecture, evaluating design and operational cost-benefit tradeoffs within systems. You will create and contribute to frameworks that enhance the efficacy of logging data, while also working with data infrastructure to triage and resolve issues. Collaboration is key, as you will engage with engineers, product managers, and data scientists to understand data needs and represent key insights visually in a meaningful way. You will define and manage service level agreements (SLAs) for all data sets within your areas of ownership, implement security models based on privacy requirements, and ensure that data quality issues are addressed while evolving governance processes. Your responsibilities will also include designing, building, and launching sophisticated data models and visualizations that support various use cases across different products or domains. You will solve complex data integration problems using optimal ETL patterns and frameworks, and assist in optimizing existing processes running in production. Additionally, you will have the opportunity to mentor team members by providing and receiving actionable feedback, influencing product and cross-functional teams to identify data opportunities that drive impact. This role is ideal for someone who thrives in a fast-paced environment and is passionate about leveraging data to inform product decisions and enhance user experiences.

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 working with data infrastructure to triage issues and resolve.
• Collaborate with engineers, product managers, and data scientists to understand data needs and represent key data insights visually.
• 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, and address data quality issues.
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains.
• Solve challenging data integration problems utilizing optimal ETL patterns, frameworks, and query techniques.
• 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 and receiving actionable feedback.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 5+ years experience in the data warehouse space.
• 5+ years experience in custom ETL design, implementation, and maintenance.
• 5+ years experience with object-oriented programming languages.
• 7+ years experience with schema design and dimensional data modeling.
• 7+ years experience in writing SQL statements.
• Experience analyzing data to identify gaps and inconsistencies.
• Experience managing and communicating data warehouse plans to internal clients.

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, data privacy.
• Experience working with terabyte to petabyte scale data.
• Experience influencing product decisions with data.