Senior Data Automation Engineer

Adobe Adobe · Enterprise · San Jose, CA +7

Senior Data Automation Engineer at Adobe to build agentic AI-powered workflows for streamlining reporting, governance, and data validation in post-sales marketing operations. Responsibilities include exploring customer datasets, designing scalable ETL/ELT pipelines, developing automation workflows, and partnering with business teams. Requires 5+ years of data engineering experience, Python/SQL proficiency, experience with cloud data platforms and orchestration tools, and demonstrated experience with agentic AI frameworks.

What you'd actually do

  1. Explore and profile customer datasets to identify, evaluate, and document data sources, accelerating their ingestion into our Customer Data Foundation for use in customer learning initiatives.
  2. Design and build scalable ETL/ELT pipelines that ingest, transform, and deliver data across Adobe Experience League's MarTech platforms (Adobe Analytics, AEM, Marketo, AEP, and internal systems).
  3. Develop and maintain automation workflows that reduce manual data handling, accelerate analysis efforts, and improve data quality across the marketing tech stack.
  4. Partner with marketing, content, and analytics partners to translate business requirements into robust data engineering solutions.

Skills

Required

  • 5+ years of experience in data engineering, data automation, or a related field with a strong emphasis on automation and system development.
  • BS/MS or equivalent experience in Computer Science, Data Engineering, Information Systems, or equivalent practical experience required
  • Proficiency in Python and SQL
  • experience building production-grade data pipelines using tools such as Apache Airflow, dbt, or equivalent orchestration frameworks.
  • Experience working with cloud data platforms (Snowflake, Databricks, or AEP) and understanding of data modeling methodologies.
  • Ability to translate loosely defined marketing and business needs into well-scoped technical requirements and reliable data pipelines.
  • Demonstrated experience building or working with agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI) or LLM-powered automation tools to drive workflow efficiency.
  • Strong communication skills

What the JD emphasized

  • agentic AI-powered workflows
  • agentic AI frameworks

Other signals

  • agentic AI-powered workflows
  • streamline reporting, governance, and data validation
  • build clean, scalable data systems
  • ETL/ELT pipelines
  • automation workflows
  • agentic AI frameworks