Description

Responsibilities

• Design, develop, and maintain scalable data pipelines and data products using Azure Databricks and modern Data & AI engineering practices.
• Implement and optimize data ingestion, transformation, and orchestration frameworks using PySpark, SQL, Python, and Azure Data Factory.
• Build and manage curated data layers following Medallion Architecture (Bronze, Silver, Gold).
• Develop semantic models, business-ready datasets, and governed data products to support analytics and AI use cases.
• Implement and support Databricks Genie for conversational analytics and self-service business intelligence.
• Collaborate with architects, business analysts, and stakeholders to translate business requirements into scalable technical solutions.
• Integrate and model data from marketing platforms including Salesforce, Marketo, Google Ads, LinkedIn Ads, and Bing Ads.
• Ensure data quality, performance optimization, governance, and security using Unity Catalog and industry best practices.
• Support AI-powered analytics, GenAI, and conversational BI initiatives by enabling AI-ready data foundations.
• Mentor junior engineers, conduct code reviews, and promote engineering best practices across the team.
• Participate in Agile ceremonies, sprint planning, backlog refinement, and release activities.

Experience

• 7+ years of experience in Data Engineering and cloud-based analytics solutions.
• 3+ years of hands-on experience with Azure Databricks and modern data platforms.
• Experience delivering enterprise-scale data, analytics, or AI solutions.
• Experience in Marketing Analytics, Customer Analytics, or Digital Marketing domain is highly preferred

Key Skills

Education

Bachelor's degree