Senior Data Engineer

Adobe•San Francisco, CA

12d•$133,100 - $236,400

About The Position

The world of design is changing rapidly and the Pro Design team is leading that transformation. We are the Adobe organization behind Illustrator, InDesign, and emerging experiences that connect creativity, collaboration, and AI. Our teams are reimagining what professional design looks like for the next decade - building intelligent, connected tools that empower creators and teams to move faster without sacrificing craft. We are looking for a Senior Data Engineer who will build a strong and scalable foundation to support it. Join us and build Adobe’s future products!

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
Proficiency in SQL and Python, PySpark, Airflow, Databricks workflows.
5+ years in data engineering, including production pipelines at scale.
Experience with high-volume event/telemetry data from a client application, not just server-side data.
Experience integrating AI tools to optimize/redesign workflows towards higher efficiency, quality, or latency.
Experience building multi-agent AI systems or agentic workflows.
Working knowledge of AI/ML data pipelines (feature stores, embeddings, or retrieval) and modern BI/reporting tools.
A track record of partnering with Product, Engineering, and Data Science to turn ambiguous questions into reliable data models.

Nice To Haves

MS or Ph.D. in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
Hands-on experience with Databricks and Unity Catalog (or comparable Lakehouse and governance tooling).
Experience deploying and managing services and applications on Azure and Azure Cloud platforms.
Familiarity with Retrieval Augmented Generation (RAG) techniques working in conjunction with LLMs.
Familiarity with data privacy and compliance for user-behavior data (e.g., GDPR, CCPA).

Responsibilities

Build, scale and optimize the data architecture and ETL/pipeline on Databricks across Pro Design products, spanning shared platform data and in-app usage telemetry.
Partner with Product, Engineering, and Data Science to define and implement data logging and instrumentation that enables product experimentation, AI/ML features, and analytics.
Set and evolve governance standards regarding data quality, privacy, security, lineage, and SLAs in Unity Catalog.
Build automated reporting and the data foundations that power conversational, AI-driven insights across our reporting stack.
Keep production pipelines and queries healthy and performant at scale and drive optimization for cost and latency.