Job
                                Description
                            
                            
                                Data Engineer (Manager Level Individual Contributor)Experience: 5 8 yearsLocation: Noida, UPRole Type: Individual Contributor (IC)About the RoleWe are seeking a highly skilled Data Engineer with strong Python development expertise and proven experience in building and scaling cloud-based data management platforms. This role requires hands-on expertise in data pipelines, data lakehouse architectures, and Apache Spark, with a strong foundation in metadata and master data management. The ideal candidate will also bring experience in AI-driven analytics and demonstrate the ability to design, optimize, and manage data solutions with a focus on cost efficiency.Key ResponsibilitiesDesign, build, and maintain scalable data pipelines and ETL/ELT processes across Azure-based ecosystems.Develop and optimize data lakehouse solutions leveraging Azure Synapse Analytics, Microsoft Fabric, and Databricks.Estimate and manage cloud resource utilization and costs for data pipelines, ensuring efficiency and cost-effectiveness.Monitor and fine-tune pipelines to balance performance and cost optimization across compute, storage, and data movement.Collaborate with analytics teams to deliver business-ready datasets for reporting and AI-driven use cases.Implement best practices for metadata and master data management, ensuring data lineage, quality, and governance.Develop and support real-time and batch processing frameworks using Apache Spark.Integrate and support visualization solutions using Power BI for business stakeholders.Partner with data science and AI teams to enable AI/ML-powered analytics solutions.Ensure adherence to data security, compliance, and governance standards.Required Qualifications5 8 years of hands-on experience as a Data Engineer or similar role.Strong Python coding expertise for data processing and automation.Proven experience with Azure Synapse, Microsoft Fabric, and Databricks in enterprise environments.Hands-on expertise with Apache Spark, distributed data processing, and performance optimization.Experience in cost estimation, monitoring, and optimization of cloud-based pipelines.Proficiency in Power BI and data visualization best practices.Strong knowledge of metadata management, master data management, and data governance frameworks.Exposure to AI-driven analytics and integration with ML/GenAI workflows.Solid understanding of data modeling, data quality, and data integration principles.Preferred SkillsFamiliarity with CI/CD pipelines for data engineering (Azure DevOps, GitHub Actions, etc).Experience with API-driven data ingestion and workflow orchestration tools.Knowledge of responsible AI practices and explainability frameworks.Strong problem-solving, communication, and stakeholder management skills. ;