Senior Data Engineer - Data Products & AI

Adobe Adobe · Enterprise · San Jose, CA +1

Senior Data Engineer focused on building data products for AI consumption, architecting scalable data pipelines, and developing AI agents and automation solutions using modern data platforms and AI tools.

What you'd actually do

  1. Build data products that are optimized for both human and AI consumption, ensuring seamless usability, accessibility, and integration across diverse workflows.
  2. Drive the implementation of innovative data warehousing strategies, ensuring efficient data storage, retrieval, and transformation processes.
  3. Architect and optimize scalable data pipelines and models to handle the exponential growth of data and analytics needs.
  4. Lead the design and development of robust software solutions, ensuring high-quality code, thorough testing, and comprehensive documentation.
  5. Spearhead initiatives to enhance developer productivity and streamline engineering workflows through innovative automation and AI-powered solutions.

Skills

Required

  • 10+ years of experience in data engineering and software development
  • Bachelor’s degree in Computer Science, Engineering, or a related field
  • Designing and deploying scalable data solutions using SQL and Python
  • Data architecture, data modeling, warehousing principles, efficient data transformation pipelines
  • Modern data platforms and tools (Databricks, Azure, Airflow)
  • Building conversational and workflow automation AI agents in production environments
  • Using AI tools (e.g. Cursor) to more efficiently build production-worthy applications and data pipelines
  • Standard engineering productivity tools (GitHub, JIRA, Confluence)

Nice to have

  • Mentoring peers
  • Passion for mentoring and fostering a culture of creativity and excellence

What the JD emphasized

  • Experience building conversational and workflow automation AI agents in production environments
  • Proven expertise in designing and deploying scalable data solutions using SQL and Python, with a focus on automation, data transformation, and advanced analytics
  • In-depth knowledge of data architecture, including data modeling, warehousing principles, and the development of efficient data transformation pipelines
  • Exceptional problem-solving skills, a critical perspective and the ability to challenge conventional approaches to drive innovation

Other signals

  • Build data products optimized for AI consumption
  • Experience building conversational and workflow automation AI agents in production environments
  • Use AI tools to more efficiently build production-worthy applications and data pipelines