Lead the design and development of enterprise-grade data engineering solutions using Microsoft Fabric and Azure. Collaborate with architects and stakeholders to implement scalable data pipelines, data models, and governance practices.
LEAD DATA ENGINEER – MICROSOFT FABRIC & AZURE
HSO India Pvt. Ltd.
Experience
10+ Years
Work Mode
Remote / Work From Home
Notice Period
Immediate to 30 Days
Employment Type
Full-Time
Salary
Best in the Market
About the Role
HSO is looking for an experienced Lead Data Engineer with 10+ years of experience in designing, developing, and implementing scalable data engineering solutions. The ideal candidate will have strong hands-on expertise in Microsoft Fabric and Microsoft Azure, along with experience in modern data platforms, data pipelines, data warehousing, ETL/ELT, and cloud-based data engineering.
Microsoft Fabric and Microsoft Azure are MANDATORY requirements for this position.
Key Responsibilities
Lead the design and development of enterprise-grade data engineering solutions using Microsoft Fabric and Azure.
Design scalable and reliable data pipelines for batch and real-time data processing.
Develop and optimize ETL/ELT processes using modern Azure and Microsoft Fabric technologies.
Work extensively with Microsoft Fabric Data Factory, Lakehouse, Data Warehouse, OneLake, and related Fabric components.
Design and implement solutions using Azure Data Factory, Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure SQL, and other Azure data services.
Develop data ingestion, transformation, cleansing, and integration processes from multiple source systems.
Implement data models and data warehouse solutions supporting analytics and reporting requirements.
Optimize data pipelines, queries, storage, and processing performance.
Establish data quality, security, governance, and monitoring practices.
Collaborate with Data Architects, Solution Architects, BI Developers, and business stakeholders.
Provide technical leadership and mentoring to data engineering teams.
Participate in solution design, estimation, code reviews, troubleshooting, and production support.
Mandatory Skills – Microsoft Fabric
Strong hands-on experience with Microsoft Fabric Data Factory.
Hands-on experience with Fabric Lakehouse and Fabric Data Warehouse.
Strong understanding of OneLake.
Experience with data pipelines, notebooks, and Dataflows Gen2.
Experience with Fabric architecture, workspace management, data ingestion, transformation, and optimization.
Mandatory Skills – Microsoft Azure
Strong hands-on experience with Azure Data Factory (ADF).
Azure Data Lake Storage Gen2.
Azure Synapse Analytics and Azure SQL.
Azure Databricks and Azure Storage.
Azure Functions / Logic Apps.
Azure Key Vault, monitoring, and security services.
Technical Skills
10+ years of experience in Data Engineering / Data Platform development.
Strong SQL and database development skills.
Experience with Python and/or PySpark.
Strong understanding of ETL/ELT and data pipeline development.
Experience with Data Warehousing, dimensional modelling, and Lakehouse architecture.
Knowledge of batch and real-time data processing.
Experience with APIs, structured and unstructured data sources.
Experience with Git, CI/CD, and DevOps practices.
Knowledge of data security, governance, lineage, and data quality.
Experience troubleshooting and optimizing complex data pipelines.
Leadership & Collaboration
Proven ability to lead technical discussions and data engineering initiatives.
Ability to translate business requirements into scalable technical solutions.
Strong stakeholder management and communication skills.
Experience mentoring data engineers.
Ability to work independently in a remote environment.
Strong analytical and problem-solving capabilities.
Preferred / Good-to-Have Skills
Microsoft Certified: Azure Data Engineer Associate or equivalent certification.
Experience with Power BI and Microsoft Power Platform.
“I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!”