Data Engineer, Analytics

$212,109 - $235,400/Yr

Meta - Phoenix, AZ

Full-time - Mid Level

Remote - Phoenix, AZ

5,001-10,000 employees

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About the position

The Data Engineer, Analytics role at Meta involves designing and implementing data warehousing activities to support informed decision-making across various products and domains. The position requires collaboration with cross-functional teams to understand data needs and create sophisticated data models and visualizations. The role also emphasizes data governance, security, and optimization of data pipelines and systems.

Responsibilities

• Design, model, and implement data warehousing activities to deliver the data foundation that drives impact through informed decision making.
• Design, build and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains.
• Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way.
• Define and manage SLA for all data sets in allocated areas of ownership.
• Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve.
• 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.
• Solve challenging data integration problems utilizing optimal ETL patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
• 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.
• Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors.
• Demonstrate good judgment in selecting methods and techniques for obtaining solutions.

Requirements

• Master's degree in Computer Science, Engineering, Information Systems, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field.
• 24 months of experience in data ETL (extract, transform, load) design, implementation, and maintenance on a large scale.
• 24 months of programming experience in Python, Perl, Java, or PHP.
• 24 months of experience writing SQL statements.
• 24 months of experience analyzing large volumes of data to provide data-driven insights, gaps, and inconsistencies.
• 24 months of experience in data warehousing architecture (data vault 2.0 style).
• 24 months of experience in dimensional data modeling, or schema design.
• 24 months of experience with MapReduce or MPP systems.
• 24 months of experience with Hadoop, Hbase, or Hive.

Benefits

• Bonus
• Equity
• Health benefits