Solution Architect designing enterprise automation solutions at UiPath. Collaborating with clients to translate complex business requirements into architectural designs.
About the role
- Senior Data Engineer developing and optimizing enterprise-grade data solutions within Microsoft Fabric ecosystem. Collaborating with data scientists, analysts, and stakeholders for data-driven decision-making.
Responsibilities
- Design, develop, and maintain data pipelines to move data between Microsoft Fabric (Lakehouse/Warehouse) and Snowflake, often utilizing Fabric Data Factory
- Set up connectors, mirroring, or Spark notebooks to sync data from OneLake to Snowflake, including handling incremental loads
- Build and optimize data models (Star Schema/Data Vault) within Snowflake and Fabric for high-performance querying
- Monitor and optimize Fabric to Snowflake compute usage and ensure efficient data movement
- Ensure data security during transfer, using tools like Snowflake RBAC, Dynamic Data Masking, and Fabric's security features
- Design and orchestrate complex integrations across Data Factory, REST APIs, and other enterprise data services
- Develop reusable, optimized Spark jobs and configure compute pools for cost-efficient performance
- Establish naming conventions, workspace governance, and CI/CD deployment strategies across Fabric
- Build monitoring dashboards, alerts, and automated testing for pipelines and operations
- Leverage AI coding agents and AI-assisted development tools (e.g., GitHub Copilot, Windsurf, or similar) to accelerate data engineering workflows, automate repetitive tasks, and improve code quality across the Fabric ecosystem
Requirements
- 5+ years of experience working on complex data integration and pipeline development across variety of systems
- Proficient in SnowSQL, stored procedures, tasks, and data loading/unloading (COPY INTO)
- Experience with Data Factory pipelines, Dataflow Gen2, and OneLake integration
- Expertise in Spark/Python (PySpark) for data transformation, or ELT tools
- Advanced SQL knowledge is essential for complex transformations
- Ability to design and orchestrate complex data integrations, leveraging Data Factory, REST APIs, and other enterprise data sources
- Leadership in defining and executing scalable ELT strategies using Spark notebooks, Data Factory, and Synapse pipelines
- Advanced knowledge of data pipeline optimization, including performance tuning and workload configuration
- Experience establishing naming conventions, workspace governance, and CI/CD deployment strategies
- Leadership in data governance, including sensitivity classifications, security models, and access control frameworks
- Ability to build and maintain monitoring, alerting, and automated testing for ADF pipelines and data assets
- Hands-on experience using AI coding agents and AI-assisted development tools in a data engineering context
Benefits
- Flexibility: Plan your workdays in a way that suits you best
- Professional development opportunities
- Award-Winning Workplace: Proudly recognized as a Great Place to Work for 20 consecutive years
- Inclusive Culture: We are committed to an inclusive culture where every team member can be their authentic self
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