Azure Synapse & Microsoft Fabric Data Engineer
Role details
Job location
Tech stack
Job description
Role Overview
The Azure Synapse & Microsoft Fabric Data Engineer was responsible for designing, building, and optimizing data solutions across the Microsoft data ecosystem. The role covered end-to-end data engineering activities, including ingestion, transformation, orchestration, modeling, and performance tuning, supporting advanced analytics and BI workloads.
Key Responsibilities
Designed, developed, and maintained scalable data pipelines using Azure Synapse Analytics (SQL Pools, Spark Pools, Pipelines).
Implemented data workflows and transformation logic within Microsoft Fabric, including Data Factory, Lakehouse, Data Engineering, and Data Pipelines.
Created and optimized data models to support reporting, dashboards, and analytics.
Built and managed data ingestion frameworks from various on-prem and cloud sources.
Ensured data reliability, performance, and scalability through monitoring, optimization, and automation.
Applied security best practices, including RBAC, data masking, encryption, and governance via Purview.
Collaborated closely with BI teams, architects, and business stakeholders to translate data requirements into technical solutions.
Ensured proper documentation, version control, and DevOps practices (CI/CD, IaC).
Required Skills & Experience
Minimum 4+ years of hands-on experience in data engineering within the Microsoft ecosystem.
Strong expertise in:
Azure Synapse Analytics (Serverless, Dedicated SQL, Spark, Pipelines)
Microsoft Fabric (Lakehouse, Data Engineering, Data Factory)
Azure Data Lake Storage (ADLS)
Azure Data Factory
Proficiency in SQL, Python, and data transformation frameworks.
Experience with Delta Lake or parquet-based lakehouse architectures.
Solid understanding of ETL/ELT design patterns and distributed data processing.
Familiarity with Microsoft Purview or similar governance platforms.
Experience with Azure DevOps (Repos, Pipelines) or Git-based workflows.
Nice to Have
Experience with Power BI integration or Fabric semantic modeling.
Knowledge of Databricks or other cloud-based analytics platforms.
Understanding of real-time ingestion (Event Hub, Stream Analytics).
Soft Skills
Collaborative approach with strong communication skills.
Ability to work in Agile environments and deliver incremental value.
Comfortable translating business needs into technical
Requirements
Minimum 4+ years of hands-on experience in data engineering within the Microsoft ecosystem.
Strong expertise in:
Azure Synapse Analytics (Serverless, Dedicated SQL, Spark, Pipelines)
Microsoft Fabric (Lakehouse, Data Engineering, Data Factory)
Azure Data Lake Storage (ADLS)
Azure Data Factory
Proficiency in SQL, Python, and data transformation frameworks.
Experience with Delta Lake or parquet-based lakehouse architectures.
Solid understanding of ETL/ELT design patterns and distributed data processing.
Familiarity with Microsoft Purview or similar governance platforms.
Experience with Azure DevOps (Repos, Pipelines) or Git-based workflows.
Nice to Have
Experience with Power BI integration or Fabric semantic modeling.
Knowledge of Databricks or other cloud-based analytics platforms.
Understanding of real-time ingestion (Event Hub, Stream Analytics).
Soft Skills
Collaborative approach with strong communication skills.
Ability to work in Agile environments and deliver incremental value.
Comfortable translating business needs into technical
