Senior Data Engineer

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Senior Data Engineer

Role Overview

• We are looking for a Senior Data Engineer to support the Data Engineering ecosystem for Content Operations and Site Quality . The role will involve managing and enhancing large-scale data pipelines, data models, analytics infrastructure, and AI-driven solutions that support business and analytics teams.

• The ideal candidate will have strong hands-on experience in SQL, PySpark, data engineering, cloud/data platforms , and a working understanding of Adobe Analytics and AI/LLM-based solutions .

• Key Responsibilities

• Data Engineering & Platform Management (Must have)

• Own and manage Data Engineering activities supporting Content Ops and Site Quality.

• Develop, maintain, and optimize data pipelines supporting approximately 150 MDP tables, 2 SSAS Cubes, and multiple Airflow workflows .

• Build and maintain scalable data processing solutions using SQL Server, Iceberg, PySpark, ECS, and Airflow .

• Troubleshoot data quality, pipeline, performance, and production issues and drive them through to resolution.

• Support data modeling and development of reliable datasets for downstream analytics and reporting.

• AI & Analytics Solutions (Preferred)

• Develop and enhance AI/LLM-based solutions , including RAG and agent-based applications.

• Contribute to an AI agent/RAG solution that enables users to translate Adobe Analytics requirements into SQL queries .

• Maintain and enhance the Client’s chatbot assistant , including updates, new capabilities, and ongoing performance improvements.

• Identify opportunities to leverage AI and automation to simplify data and analytics workflows.

• Stakeholder & Solution Development

• Partner with business and analytics stakeholders to understand requirements and translate them into scalable technical solutions.

• Contribute to solution design, technical discussions, and roadmap development.

• Clearly communicate complex technical concepts and solutions to non-technical stakeholders.

• Required Skills & Experience

• Strong 3-5 Years hands-on experience in Data Engineering with SQL and PySpark .

• Experience with SQL Server, SSAS, Airflow , and modern data platforms.

• Experience working with Iceberg and cloud/container-based environments such as ECS .

• Strong understanding of data modeling, ETL/ELT, data pipelines, and data quality .

• Experience with Adobe Analytics or similar digital analytics platforms.

• Exposure to AI/LLM solutions, RAG, AI agents, or Generative AI applications .

• Strong problem-solving and troubleshooting skills.

• Ability to work independently and manage multiple production-critical data assets.

• Preferred Skills

• Experience building RAG/agentic AI applications using LLMs.

• Experience converting business/analytics requirements into SQL and data solutions .

• Experience with APIs, Python, and cloud technologies.

• Experience developing stakeholder-facing analytics or AI solutions.

• Strong communication and stakeholder management skills.

📩 Interested candidates, please share your updated resume at: [email protected]