Data Engineer, Product Analytics

$109,000 - $166,000/Yr

Meta - Lansing, MI

Full-time - Mid Level

Lansing, MI

Web Search Portals, Libraries, Archives, and Other Information Services

About the position

The Data Engineer for Product Analytics at Meta plays a crucial role in optimizing growth, strategy, and user experience for over 3 billion users. This position involves collaboration with software engineering, data science, and product management teams to tackle significant data challenges. The engineer will manage data warehouse plans, ensure data availability, and implement data models and visualizations, directly impacting company growth and user satisfaction.

Responsibilities

• 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.
• Collaborate with engineers, product managers, and data scientists to understand data needs and represent key data insights meaningfully.
• 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.

Requirements

• 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.).

Nice-to-haves

• 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.

Benefits

• Bonus
• Equity
• Health benefits