Senior Data Engineer

Posted 94ds ago

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Job Description

Senior Data Engineer architecting and scaling systems for AI-driven tools at WAG. Collaborating with teams to transform fragmented data into a competitive advantage.

Responsibilities:

  • Design and operate scalable data ingestion and web scraping systems
  • Build batch and real-time pipelines to normalize, enrich, and version data across structured and unstructured sources
  • Develop systems to support LLM- and ML-based document parsing, OCR, and classification
  • Own the architecture of our data storage and processing stack, including PostgreSQL, data lakes, and data warehouses
  • Operationalize AI/ML workflows by preparing clean training and inference datasets with robust lineage, validation, and error handling
  • Integrate output with backend APIs, valuation services, and frontend analytics dashboards
  • Collaborate across engineering and product to ship reliable, intelligent features quickly
  • Contribute to our infrastructure tooling , including CI/CD, IaC (Terraform), and data observability

Requirements:

  • Education: B.S. in Computer Science or equivalent
  • Language : Fluency in English (written and spoken)
  • Experience: 5+ years of experience building data platforms in production environments, ideally in startup or fast-moving contexts
  • Technical Skills: Fluent in Python, SQL , and familiar with orchestration tools like Airflow, Dagster, or Temporal
  • Have designed or maintained web scraping pipelines at scale , using best practices around retries, proxies, and anti-bot strategies
  • Understand tradeoffs between ETL and ELT , and have hands-on experience with data lakes and data warehouses
  • Have integrated structured and unstructured sources , and enjoy resolving messy edge cases that come with real-world data
  • Have worked with LLM APIs or ML models in production , particularly for document understanding, NLP, or entity extraction
  • Thrive in AI-native environments and enjoy building tools that support intelligent automation and analytics
  • Care about clean architecture, versioning, reproducibility, and quality in data systems

Benefits:

  • A Welcoming Team
  • A friendly, international team working with modern, cutting-edge technologies
  • Collaborative, inclusive, and supportive company culture
  • Transparent communication and regular feedback
  • Team-building activities and virtual social events
  • Employee recognition and appreciation programs