Data Engineer, AEP

Job Overview

JOB DETAILS

REQUIREMENTS

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 8+ years of overall experience in data engineering, including ETL/ELT design, data modeling, and large-scale data architecture.
• 2+ years of hands-on experience working directly with Adobe Experience Platform, including Data Distiller, XDM, and identity stitching.
• 3+ years of experience writing and optimizing complex SQL queries, specifically in customer data and marketing analytics contexts.
• 3+ years of experience with Databricks for data transformation and processing.
• 2+ years of experience using GraphQL to interact with APIs and structured datasets.
• 2+ years of experience working with Snowflake and Enterprise Data Warehousing (EDW) systems for scalable data integration.
• 2+ years of experience working with Adobe Real-Time CDP, Customer Journey Analytics, and Adobe Launch is a plus.
• 5+ years of experience with Strong analytical and problem-solving skills and the ability to translate business requirements into technical implementations.
• 5+ years of experience with Excellent verbal and written communication and collaboration skills across technical and business teams.

RESPONSIBILITIES

• Design, develop, and maintain scalable and reusable data pipelines within Adobe Experience Platform.
• Write, optimize, and manage complex SQL queries using AEP Data Distiller to support data analysis, reporting, and audience activation.
• Model and maintain XDM schemas, datasets, and identity graphs to support consistent and unified customer views.
• Ingest data from multiple systems using both batch and streaming pipelines into AEP.
• Collaborate with cross-functional teams including marketing, analytics, and engineering to ensure data integrity and accessibility.
• Implement data governance, auditing, performance tuning, and workflow monitoring in AEP.
• Leverage Databricks for advanced data transformation and processing pipelines.
• Use GraphQL to interact with APIs and query structured datasets effectively.
• Integrate and manage datasets across Snowflake and EDW platforms for analytics and reporting use cases.
• Document all technical workflows, data mappings, and architecture components for internal and external stakeholder use.

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