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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in developing and maintaining Microsoft Fabric Lakehouse solutions, with a strong focus on data ingestion, transformation, and quality frameworks. Proficient in utilizing Spark, PySpark, and SQL for scalable data processing while adhering to data governance and security standards.
Highest-signal resume keywords
Microsoft Fabric Lakehouse DevelopmentSpark / PySpark ProficiencyData Ingestion and TransformationData Quality and Validation FrameworksMicrosoft Purview Knowledge
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringETL/ELTCDCSQLPythonDelta LakeData Quality ChecksSchema ValidationAudit LoggingException Handling
Tools & Technologies
Microsoft FabricOneLakePower BIAzure DevOpsGitCI/CDData PipelinesSynapse PipelinesNotebooksPurview
Certifications & Qualifications
Microsoft Fabric CertificationAzure Data Engineer Certification
Industry Keywords
Commercial Insurance DataBrokerage DataMedallion ArchitectureData GovernanceRBACPII/PHI Controls
Tech Stack
Tools & technologiesAzureETLGoogle Cloud PlatformPySparkPythonSparkSQL
About the role
Key responsibilities & impact- Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers
- Build reusable data ingestion pipelines and CDC frameworks for sources including GCP, CSV, Excel, email files, and SharePoint
- Implement Bronze-layer ingestion with audit logging, schema validation, schema-drift detection, and error handling
- Develop Silver-layer transformations for cleansing, standardization, data quality, validation, and exception handling
- Build Gold-layer datasets including curated entities, conformed dimensions, business metrics, KPIs, aggregations, and secure views
- Develop and optimize Spark / PySpark, Python, and SQL workloads for scalable data processing
- Build data pipelines using Fabric Data Pipelines, Synapse Pipelines, and Notebooks
- Support Power BI semantic models and Direct Lake data consumption requirements
- Implement data quality checks, reconciliation processes, monitoring, and operational controls
- Follow data governance and security standards, including Purview, RBAC, PII/PHI controls, classification, and lineage
- Troubleshoot pipeline failures, performance issues, data discrepancies, and production incidents
- Collaborate with Solution Architects, Lead Data Engineers, BI teams, and business stakeholders to deliver scalable data solutions
Requirements
What you’ll need- 8+ years of overall Data Engineering experience with hands-on experience in Azure / Microsoft Fabric
- Strong hands-on experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks
- Proficiency in Spark / PySpark, Python, SQL, and Delta Lake
- Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture
- Experience developing data quality, validation, reconciliation, and exception-handling frameworks
- Knowledge of Power BI semantic models and Direct Lake
- Experience with Microsoft Purview, Azure DevOps, Git, CI/CD, and deployment
- B.Tech / Bachelor’s degree or equivalent in Computer Science, Engineering, Information Technology, or a related field
- Commercial insurance or brokerage data experience preferred
- Microsoft Fabric or Azure Data Engineer certification preferred
Benefits
Comp & perks- Hybrid work arrangement