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About the role
Position Summary: The Data Engineer will design, build, and optimize scalable data pipelines and curated data products within a up-to-date Lakehouse architecture (Databricks). This role is responsible for delivering high-quality, business-ready datasets (gold layer) that power enterprise analytics and Power BI reporting. The ideal candidate has deep Databricks experience, solid data modeling skills, and a focus on building reliable, testable, and governed data solutions. Exposure to AI-driven development or AI agents is a plus. Work Youll Do: Data Engineering & Pipeline Development Design, develop, and maintain scalable data pipelines using Databricks and Delta Lake Build and manage transformations across bronze, silver, and gold layers Optimize processing for performance, reliability, and cost Integrate data from ERP, CRM, APIs, and other enterprise systems Data Modeling & Business Logic Develop gold-layer datasets aligned to standardized business definitions Translate business requirements into reusable data models Ensure consistency of core metrics across reporting Align Databricks outputs with Power BI semantic models Data Quality, Testing & Reliability Implement automated data quality checks and validation rules Build testable, production-ready pipelines Support impact analysis using lineage tools Participate in CI/CD and deployment processes Performance Optimization & Operations Monitor and optimize pipeline performance Troubleshoot issues across settings Ensure data consistency between dev, test, and prod Support high-volume data workloads AI & Automation (Preferred) Use AI-assisted tools for development (e.g., Copilot, Databricks Agents) Explore AI agents for testing, lineage analysis, and optimization Contribute to AI-driven engineering practices Collaboration & Stakeholder Engagement Partner with BI and business teams Support governance and cataloging efforts Document data models and pipelines Basic Qualifica .