Data Science Engineer
Core
Build large-scale cloud-based data and analytics platforms, data pipelines, and production-grade ML model integrations to drive personalization and automated data operations for Adobe's enterprise-wide consumers.
Role type
Senior Data Science Engineer (Data Engineering focus)
Builds
Fault-tolerant scalable data pipelines, analytical personalization capabilities, LLM agents, and end-to-end data pipelines for ML models.
Domain
Digital experiences, personalization, cloud data engineering, machine learning operations
Deliverable
production ML models | infrastructure
Required skills
Distributed data technologies (Hadoop, Hive, Presto, Spark), Cloud technologies (Databricks, S3, Azure Blob Storage, AWS EMR, Athena, Glue), Streaming data ingestion (Kafka, Kinesis), SQL, Python/PySpark/Scala, CI/CD tools, Open-source orchestration tools (Apache Airflow, Azkaban)
Preferred skills
LLM Models/Agentic workflows, Prompt engineering, RAG, Knowledge graphs, Data Governance tools, Adobe solutions (AEP, AJO, CJA)
Technologies
Hadoop, Hive, Presto, Spark, Databricks, S3, Azure Blob Storage, AWS EMR, Athena, Glue, Kafka, Kinesis, Delta, Parquet, ORC, GitHub, Jenkins, Apache Airflow, Azkaban, Python, PySpark, Scala, Pandas, NumPy, Koalas, AEP, AJO, CJA
Responsibilities
Build fault-tolerant scalable data pipelines using cloud-based tools; Build analytical personalization capabilities using modern technologies; Build LLM agents to optimize and automate data pipelines; Deliver End to End Data Pipelines to run Machine Learning Models in a production platform; Architect data ingestion, transformation, consumption, and governance frameworks; Help build production grade ML models and integration with operational systems.
Seniority
Senior, hands-on IC
