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Data Engineer, Product Analytics

Meta
London, GBR
Full-time
Mid · 4+ years experience
Onsite
Discovered 1 weeks ago
SQLETLPythonC++C#Scala
Free

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Responsibilities

  • Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
  • 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, representing key data insights in a meaningful way
  • Define and manage Service Level Agreements for all data sets in allocated areas of ownership
  • 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
  • Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
  • Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
  • 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 providing actionable feedback

Minimum Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent
  • 4+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions
  • 4+ years of experience (or 2+ years with a Ph.D) with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)

Preferred Qualifications

  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Master's or Ph.D degree in a STEM field
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

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