Senior Data Science Engineer

About the Role Adobe is seeking a highly skilled Senior Data Engineer to join our Doc Cloud Product & Business Analytics organization. This role focuses on building and operating large-scale analytical data pipelines and analytics-ready data tables that power product adoption, usage metrics, experimentation (A/B testing), and executive dashboards across a massive monthly active user base. You will work primarily on Azure Databricks, playing a key role in setting up and evolving our Databricks-based analytics data warehouse , including curated tables, metric foundations, and scalable data models. This role is ideal for a hands-on data engineer with deep expertise in SQL, Python, Spark, and Delta Lake , and a strong understanding of analytics-driven data warehousing and product analytics. Key Responsibilities Design, build, and maintain large-scale, production-grade data pipelines on Azure Databricks using Apache Spark and Python Write and optimize complex, high-performance SQL for data transformation, aggregation, and analytics workloads at scale Develop and maintain analytics-ready data models (fact tables, dimensions, rollups, metric layers, and gold layer tables) used for dashboards and reporting Optimize Databricks workloads for performance, reliability, and cost efficiency , including tuning Spark jobs and Delta Lake tables Establish and apply Delta Lake best practices , including incremental and idempotent processing, MERGE patterns, partitioning, and table optimization. Partner closely with product analysts, business analysts, data scientists, and product managers to enable reliable, self-serve analytics, supporting product-led growth use cases. Implement data quality checks, validation frameworks, and monitoring to ensure accurate and trusted analytics metrics Apply strong Data engineering best practices , including version control and documentation Contribute to solutions that integrate structured and unstructured data , including selective use of GenAI / LLM-based capabilities where relevant Required Qualifications Education Bachelor’s degree or higher in Computer Science, Engineering, or a related field Experience 6–12 years of professional experience in Data Engineering Proven experience building and supporting production-grade analytical data pipelines at scale Technical Expertise (Must-Have) Expert-level SQL skills, including complex joins, window functions, performance tuning, and large-scale aggregations Advanced Python proficiency for data processing, pipeline development, and automation Deep hands-on experience with Azure Databricks and Apache Spark Strong understanding of Delta Lake and optimization techniques (partitioning, Z-ordering, compaction) Experience designing data models optimized for analytics and BI consumption Cloud & Platform Strong experience with Microsoft Azure , including data lake storage and access controls Familiarity with lakehouse architectures and enterprise data governance concepts Preferred Qualifications Experience with streaming or near–real-time data pipelines on Databricks Prior experience supporting product analytics, feature adoption, or MAU-based metrics Exposure to MLOps, LLM deployment, or GenAI-enabled data applications Familiarity with BI tools such as Tableau or Power BI and their performance considerations Experience mentoring analysts or junior data engineers 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 th ... (truncated, view full listing at source)