Senior Data Engineer

About the Role We are looking for a Senior Data Engineer to join our Data & Analytics Engineering team. In this role, you will develop and maintain scalable data pipelines that support product usage reporting and enterprise analytics across our products. You will operate where data architecture, data quality, and multi-functional ownership meet to ensure data is trusted, validated, and reliably delivered from product instrumentation to executive dashboards. Key Responsibilities Data Architecture & Pipeline Engineering Build and implement end-to-end data pipelines spanning product instrumentation, ingestion, transformation, semantic modeling, and reporting layers (e.g., Power BI). Develop and maintain documentation for source-of-truth datasets, including ownership of metric definitions, data joins, schema transformations, and lineage tracking. Lead data modeling efforts, including entity relationship build, dimensional modeling, and consumption-layer optimization. Data Governance & Ownership Establish and maintain clear ownership models across the data lifecycle — from ingestion to semantic model to reporting. Define RACI frameworks for data accountability, clarifying which roles are responsible, accountable, consulted, and informed at each stage. Ensure downstream teams are proactively notified and protected when upstream schema or logic changes occur. Data Quality & Validation Build and enforce data validation strategies at the pipeline level and at semantic/reporting consumption layers. Define and implement quality gates that must pass before dashboards or metrics are considered production-ready. Build monitoring, alerting, and anomaly detection systems to proactively surface data quality issues. Conduct root-cause analysis on data incidents and drive resolution across teams. Collaboration & Partner Enablement Act as a technical point of contact between Data Engineering, Product, Analytics, and BI teams. Mentor junior data engineers and contribute to team standards and ongoing skill development. Participate in architectural reviews and sign-off processes for new data products and features. Qualifications 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. Strong communication skills — able to clearly explain data concepts and architectural decisions to technical and non-technical audiences. Preferred Qualifications Experience with product usage / event data (e.g., Amplitude, Segment, Adobe Analytics, or custom instrumentation). Familiarity with data contracts, schema registries, or data mesh principles. Experience with Power BI dataflow, datasets, or enterprise-scale report delivery. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000 employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere ... (truncated, view full listing at source)