EH – Sr. Fabric Engineer – Job7247

Summary

We are seeking a highly skilled and experienced Senior Microsoft Fabric Engineer to join our dynamic team. This role is critical in driving the design, development, and implementation of scalable, robust data solutions leveraging Microsoft Fabric and Azure services. As a senior engineer, you will play a pivotal role in shaping our data architecture, enabling advanced analytics, and automating data processes to support business intelligence and decision-making. Your expertise will ensure the reliability, scalability, and efficiency of our data pipelines and platforms, while collaborating closely with cross-functional teams to deliver impactful data-driven solutions.

Responsibilities

• Lead the design, development, and deployment of scalable data solutions using Microsoft Fabric and Azure cloud services.
• Architect and implement advanced analytics solutions that empower business insights and data-driven decision-making.
• Develop, maintain, and optimize data pipelines and workflows using SQL, Python, and related technologies to automate data ingestion, transformation, and processing.
• Manage and enhance data architectures, ensuring high availability, scalability, and performance across data lakes, warehouses, and fabric environments.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.
• Provide technical leadership and mentorship to junior engineers and cross-functional teams, fostering best practices in data engineering and architecture.
• Implement and maintain CI/CD pipelines to streamline deployment and integration of data solutions.
• Monitor and troubleshoot data platform issues, ensuring data quality, security, and compliance with organizational standards.
• Stay current with industry trends, emerging technologies, and best practices in data engineering, cloud services, and Microsoft Fabric ecosystems.
• Contribute to documentation, knowledge sharing, and continuous improvement initiatives within the data engineering team.

Requirements

Must-Have Skills

• Microsoft Fabric: Expertise in Microsoft Fabric for building distributed, scalable data solutions. Experience with fabric services, microservices architecture, and managing stateful/stateless services within the fabric environment.
• Azure Service Fabric: Deep understanding of Azure Service Fabric for deploying and managing scalable, reliable microservices and containers in the cloud.
• Azure Data Lake: Proficient in designing and managing Azure Data Lake storage solutions to handle large-scale data ingestion and storage with optimized performance.
• Azure Synapse Data Engineering: Skilled in using Azure Synapse Analytics for data integration, big data processing, and building end-to-end data engineering pipelines.
• Azure Synapse Data Warehouse: Experience in designing and optimizing data warehouse solutions within Azure Synapse to support complex queries and analytics workloads.
• Power BI: Ability to integrate and visualize data using Power BI, creating interactive dashboards and reports that provide actionable insights.
• SQL Server & SQL: Strong command of SQL Server and advanced SQL querying skills for data manipulation, transformation, and performance tuning.
• Python: Proficient in Python programming for data automation, scripting, and developing data processing workflows.
• Data Architecture: Expertise in designing scalable, maintainable, and secure data architectures that align with business goals and technical requirements.
• Data Modeling: Skilled in creating logical and physical data models to support efficient data storage, retrieval, and analytics.
• Database Design: Experience in designing relational and non-relational databases optimized for performance and scalability.
• CI/CD Pipelines: Knowledge of continuous integration and continuous deployment practices to automate testing, deployment, and monitoring of data solutions.
• SSIS (SQL Server Integration Services): Proficient in using SSIS for data extraction, transformation, and loading (ETL) processes within Microsoft environments.

Nice-to-Have Skills

• PySpark: Familiarity with PySpark for big data processing and distributed computing within Spark ecosystems.
• Azure Data Factory: Experience with Azure Data Factory for orchestrating and automating data workflows and pipelines across cloud services.
• Azure Platform Services: General knowledge of Azure platform services such as Azure Functions, Logic Apps, and Event Grid to enhance data processing and integration capabilities.

Expected Duration: 6 to 11 months
Time Zone: EST