Microsoft Fabric Senior Data Engineer

Job Title: Sr. Data EngineerWork Experience: 4-6 Years (Senior)Work Experience: 2 to 3+ years (Mid-Level)Work Experience 0 1+ years (Junior)Work Location: India or MalaysiaContract Tenure: Permanent after probationary periodKey ResponsibilitiesDesign, develop, and maintain end-to-end data pipelines using Microsoft FabricParticipate in data modelling activities using star and snowflake schemasImplement and manage Medallion Architecture (Bronze, Silver, Gold layers) to ensure scalable and governed data processingApply data cleansing in silver layers and business-ready gold-datasets for optimizing analyticsImplement quality checks, validation rules, and reconciliation processesDesigned and delivered dbtdriven Medallion Architecture (reusable dbt models, macros, and tests, enforcing data quality, scalability, and transformation standards).Implemented CI/CD deployment pipelines on Microsoft Fabric, enabling automated build, test, and deployment of Fabric artifacts (Lakehouse, notebooks, pipelines, semantic models) across environmentsIngest data from multiple source systems (databases, files, APIs, cloud storage) using Fabric Data FactoryBuild and manage Fabric Lakehouse solutions leveraging OneLakeDevelop data transformation logic using PySpark and SQL for large datasetsMonitor pipeline execution, handle failures, and implement robust error handlingWork closely with business stakeholders to translate data requirements into technical solutionsEnsure data security, access control, and compliance with governance standardsDocument data flows, transformations, and architecture decisionsPerform root cause analysis for data issues and implement preventive fixesSupport production deployments and post-release issue resolutionContinuously evaluate and adopt best practices for Microsoft Fabric and analytics engineeringCollaborate with BI teams to support Power BI Direct Lake and semantic modelsRequired Skills & Experience4 to 6 years of hands-on experience in Data Engineering or Analytics EngineeringProven experience working on modern cloud-based data platformsStrong hands-on experience with Microsoft Fabric, LakeHouse mindset.Solid understanding and practical implementation of Medallion ArchitectureProficiency in Spark, PySparkStrong SQL knowledge for data transformation and analysisStrong in CI/CD automatic deployment pipelines.Experience building and managing ETL / ELT pipelinesMicrosoft Fabric certifications (DP - 700) (Azure)Data Engineering SkillsData modelling for analytics (star and snowflake schemas)Experience with batch and incremental processingData quality, validation, and reconciliation techniquesPerformance optimization and troubleshootingGood to HaveHaving experience to build dbt-driven end-to-end pipelinesPower BI experience (Direct Lake preferred) Job Title: Sr. Data EngineerWork Experience: 4-6 Years (Senior)Work Experience: 2 to 3+ years (Mid-Level)Work Experience 0 1+ years (Junior)Work Location: India or MalaysiaContract Tenure: Permanent after probationary periodKey ResponsibilitiesDesign, develop, and maintain end-to-end data pipelines using Microsoft FabricParticipate in data modelling activities using star and snowflake schemasImplement and manage Medallion Architecture (Bronze, Silver, Gold layers) to ensure scalable and governed data processingApply data cleansing in silver layers and business-ready gold-datasets for optimizing analyticsImplement quality checks, validation rules, and reconciliation processesDesigned and delivered dbtdriven Medallion Architecture (reusable dbt models, macros, and tests, enforcing data quality, scalability, and transformation standards).Implemented CI/CD deployment pipelines on Microsoft Fabric, enabling automated build, test, and deployment of Fabric artifacts (Lakehouse, notebooks, pipelines, semantic models) across environmentsIngest data from multiple source systems (databases, files, APIs, cloud storage) using Fabric Data FactoryBuild and manage Fabric Lakehouse solutions leveraging OneLakeDevelop data transformation logic using PySpark and SQL for large datasetsMonitor pipeline execution, handle failures, and implement robust error handlingWork closely with business stakeholders to translate data requirements into technical solutionsEnsure data security, access control, and compliance with governance standardsDocument data flows, transformations, and architecture decisionsPerform root cause analysis for data issues and implement preventive fixesSupport production deployments and post-release issue resolutionContinuously evaluate and adopt best practices for Microsoft Fabric and analytics engineeringCollaborate with BI teams to support Power BI Direct Lake and semantic modelsRequired Skills & Experience4 to 6 years of hands-on experience in Data Engineering or Analytics EngineeringProven experience working on modern cloud-based data platformsStrong hands-on experience with Microsoft Fabric, LakeHouse mindset.Solid understanding and practical implementation o