Senior Data Engineer

Adobe Adobe · Enterprise · San Jose, CA

Senior Data Engineer role focused on building and maintaining scalable data pipelines for product usage reporting and enterprise analytics. Responsibilities include data architecture, pipeline engineering, data governance, data quality, and collaboration with product, analytics, and BI teams. Requires proficiency in SQL, data transformation frameworks, and cloud environments, with experience in semantic modeling and BI consumption layers.

What you'd actually do

  1. Build and implement end-to-end data pipelines spanning product instrumentation, ingestion, transformation, semantic modeling, and reporting layers (e.g., Power BI).
  2. Establish and maintain clear ownership models across the data lifecycle — from ingestion to semantic model to reporting.
  3. Build and enforce data validation strategies at the pipeline level and at semantic/reporting consumption layers.
  4. Act as a technical point of contact between Data Engineering, Product, Analytics, and BI teams.
  5. Mentor junior data engineers and contribute to team standards and ongoing skill development.

Skills

Required

  • Data Engineering
  • Data Architecture
  • SQL
  • Data Transformation Frameworks (dbt, Spark, Dataflow)
  • Cloud Environments (AWS, Azure, GCP)
  • Semantic Modeling
  • BI Consumption Layers (Power BI, Tableau, Looker)
  • Data Governance
  • RACI Frameworks

Nice to have

  • Product Usage/Event Data (Amplitude, Segment, Adobe Analytics)
  • Data Contracts
  • Schema Registries
  • Data Mesh Principles
  • Power BI Dataflow/Datasets/Enterprise-scale report delivery

What the JD emphasized

  • 5+ years of experience in data engineering, data architecture, or a closely related field.
  • Proficiency in unified data platforms like Databricks, Snowflake.
  • Proficiency in SQL and at least one modern data transformation framework (e.g., dbt, Spark, Dataflow).
  • Hands-on experience building and maintaining high-capacity data integration solutions in cloud environments (AWS, Azure, or GCP).
  • Experience with semantic modeling and BI consumption layers, including familiarity with tools such as Power BI, Tableau, or Looker.
  • Demonstrated ability to define and detail data ownership models, RACI frameworks, or data governance policies.