Data Science Engineer

• Build analytical, personalization capabilities using modern and brand new technologies employing Adobe tools like AEP, AJO and CJA.
• Build LLM agents to optimize and automate data pipelines following best engineering practices.
• Deliver End to End Data Pipelines to run Machine Learning Models in a production platform.
• Innovative solutions to help broader organization take significant actions fast and efficiently.
• Chip in to data engineering and data science frameworks, tools, and processes.
• Implement outstanding data operations and implement standard methodologies to use resources in an optimum way.
• Architect data ingestion, data transformation, data consumption, data governance frameworks.
• Help build production grade ML models and integration with operational systems.
• Work in a collaborative environment and contribute to the team as well as organization's success.

As a member of the Data Engineering team, you will have significant responsibility to help build large scale cloud-based data and analytics platform with enterprise-wide consumers. This role is inherently multi-functional, and the ideal candidate will work across teams. The position requires ability to own things, come up with innovative solutions, try new tools and technologies., * Master's degree or equivalent experience is preferred.

• 8+ years of consistent track record as a data engineer.
• 5+ years validated ability in distributed data technologies e.g., Hadoop, Hive, Presto, Spark etc.
• 3+ years of experience with Cloud based technologies - Databricks, S3, Azure Blob Storage, Notebooks, AWS EMR, Athena, Glue etc. Familiarity and usage of different file formats in batch/streaming processing i.e., Delta/Parquet/ORC etc.
• 2+ years' experience with streaming data ingestion and transformation using Kafka, Kinesis etc.
• Outstanding SQL experience. Ability to write optimized SQLs across platforms.
• Proven hands - on experience in Python/PySpark/Scala and ability to manipulate data using Pandas, NumPy, Koalas etc. and using APIs to transfer data.
• Experience with CI/CD tools i.e., GitHub, Jenkins etc.
• Working experience with Open- source orchestration tools i.e., Apache Air Flow/ Azkaban etc.
• Teammate with excellent communication/teamwork skills when it comes to closely working with data scientists and machine learning engineers daily.

Nice to have

• Showcase your work if you are an open - source contributor. Passion to contribute to Open-source community is highly valued.
• Experience with Data Governance tools e.g., Collibra and Collaboration tools e.g., JIRA/ Confluence etc.
• Familiarity with Adobe solutions such as Adobe Experience Platform, Adobe Analytics, Customer Journey Analytics, and Adobe Journey Optimizer is a plus.
• Experience with LLM Models/ Agentic workflows using Copilot, Claude, LLAMA, Databricks Genie etc. is highly preferred. Skills in building context and prompt engineering solutions including classical RAG, Knowledge graph, MCPs, Agentic frameworks like n8n, etc. are highly desirable.

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $109,000 -- $200,700 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

In California, the pay range for this position is $138,600 - $200,700

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

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