Adobe

Data Engineer

Adobe

full-time

Posted on:

Location Type: Office

Location: San Jose • California, Texas • 🇺🇸 United States

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Salary

💰 $113,400 - $206,300 per year

Job Level

Mid-LevelSenior

Tech Stack

ApacheAWSAzureCloudDockerETLGoogle Cloud PlatformJavaKafkaKubernetesNeo4jPythonRayScalaSpark

About the role

  • Build scalable ingestion pipelines for brand information and creative assets, ensuring freshness, reliability, and versioning.
  • Integrate and leverage systems and models from our machine learning and data science partner teams.
  • Design and maintain brand-aware data models, ontologies, and multi-modal graphs to support context linking and rich retrievals.
  • Implement hybrid storage and retrieval strategies across vector databases, graph databases, and search engines, optimizing for precision and latency.
  • Develop metadata enrichment pipelines to enhance semantic search, personalization, and optimization for RAG-based conversational systems.
  • Ensure data quality and observability by monitoring metrics for accuracy, coverage, and timeliness; build monitoring systems to track ingestion and retrieval health.
  • Collaborate with product, ML, and information retrieval teams to align data infrastructure with creative workflows.
  • Optimize pipelines using distributed/streaming systems for scale and speed.

Requirements

  • 4+ years of software development experience with 1+ year in data engineering, search relevance, or large-scale systems for conversational experiences.
  • Expertise in building reliable and innovative ETL pipelines for heterogeneous data.
  • Experience with distributed data frameworks (Spark, Flink) and streaming platforms (Kafka).
  • Proficiency in Python (preferred) or Java/Scala, with strong CS fundamentals.
  • Experience with cloud platforms (Azure, AWS, or GCP) and containerization/orchestration (Docker, Kubernetes).
  • Familiarity with modern search systems (Elastic, Vespa) and graph databases (Neo4j, TigerGraph).
  • Understanding of ML data pipelines and MLOps standards for monitoring and continuous improvement
  • Self-starter who thrives in zero-to-one environments and can make informed tradeoffs.
  • Preferred: Background in information retrieval, NLP, or cognitive computing.
  • Preferred: Experience developing, optimizing, and deploying data processing with Apache Spark/Dask/Ray.
  • Preferred: Experience with ontologies, knowledge graphs, or semantic enrichment pipelines.
  • Preferred: Degree in Computer Science, Information Systems, or related field.
Benefits
  • Pay within range varies by work location and may depend on job-related knowledge, skills, and experience.
  • Annual Incentive Plan (short-term incentives)
  • Certain roles may be eligible for long-term incentives in the form of a new hire equity award
  • Equal Employment Opportunity and accommodations for disabilities (accessibility support)
  • Employee experiences recognized and benefits implied (Adobe Life blog and meaningful benefits)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
ETL pipelinesdata engineeringsearch relevancelarge-scale systemsdistributed data frameworksstreaming platformsPythonJavaScalaMLOps
Soft skills
self-startercollaborationproblem-solvingtradeoff analysis