Senior Azure Data Engineer

Roles & Responsibilities
Design, build, and maintain scalable data solutions on Microsoft Azure to support business data needs.
Develop and manage data pipelines for ingesting, transforming, and integrating data from multiple sources.
Perform data modelling for data warehousing projects to build scalable and reliable data warehouses.
Implement data security, governance, and privacy controls across Azure data platforms.
Monitor, troubleshoot, and optimize data workflows to ensure reliability, performance, and cost efficiency.
Optimize data storage and processing solutions by leveraging Azure best practices and services.
Design and maintain end-to-end data pipelines, ensuring reliable data ingestion, transformation, and processing using Spark.
Continuously optimize data storage and processing to achieve high performance and cost efficiency across Azure data platforms.
Mandatory Technical & Functional Skills
6+ years of consulting or client service delivery experience in Azure Microsoft Data Engineering.
4+ years of experience designing and building data ingestion, processing, and analytical pipelines using SQL Server, Azure Synapse, Azure Databricks, and Microsoft Fabric.
Hands-on experience implementing ETL and data processing using Microsoft Fabric, OneLake, ADLS, Azure Data Factory, and Azure Functions.
5+ years of hands-on experience with Azure and Big Data technologies, including:
Microsoft Fabric
Azure Databricks
Python
SQL
ADLS / Blob Storage
PySpark
Spark SQL
3+ years of experience working with RDBMS technologies.
Experience with big data file formats and compression techniques.
Proficiency with developer tools such as Azure DevOps, Git, and Visual Studio Team Services (VSTS).
Bachelor's degree in Computer Science or a related discipline, or equivalent professional experience.
Preferred Technical & Functional Skills
Provide technical leadership to data engineering teams, including solution design, implementation guidance, client demonstrations, and presentations.
Strong English communication skills and client-facing experience.
Design, develop, and deploy scalable ETL pipelines on Azure using:
Azure Data Factory
Azure Synapse Analytics
Azure Functions
Notebooks
Related Azure services
Strong hands-on experience with Microsoft Fabric, including:
Medallion Architecture
Metadata-driven ingestion frameworks
Data quality frameworks
SCD Type 1 and Type 2 transformations using Fabric Notebooks or Databricks
Exposure to Microsoft Copilot and Generative AI fundamentals, with the ability to identify and apply industry-relevant AI use cases to data engineering workflows.
Relevant Microsoft role-based certifications such as DP-600, DP-700, DP-203, DP-900, AI-102, and AI-900. Power BI PL-300 certification is an added advantage.
Proficiency in Power BI for building dashboards, defining KPIs, and delivering actionable business insights.
Proficiency in data modelling and building large-scale data warehouse designs.
Strong knowledge of Azure RBAC and IAM, with experience implementing access controls, security, and compliance standards.
Experience in data governance, performance optimization, and cost-efficient, scalable Azure solutions.
Familiarity with Azure DevOps and Git.
Experience mentoring junior team members and managing data engineering projects in consulting environments.
Alignment with Microsoft's vision and roadmap, with an eagerness to adopt emerging tools across the data and AI ecosystem.

Work arrangement
Hybrid