<p><p></p><p><b>Description :</b><br/><br/>Key Responsibilities :</p><p><br/>- Lead the design, development, and optimization of large-scale data solutions using Azure Databricks, Azure Data Factory (ADF), and Azure Synapse Analytics.</p><p> </p><p><br/></p><p>- Architect and implement efficient ETL/ELT pipelines for ingesting, transforming, and processing structured and unstructured data.</p><p> </p><p><br/></p><p>- Develop scalable data processing frameworks using PySpark and Python within the Azure ecosystem.<br/> </p><p><br/></p><p>- Collaborate with data scientists, analysts, and business stakeholders to deliver reliable, high-performance data solutions.</p><p><br/></p><p>- Ensure best practices in data governance, performance tuning, and cost optimization across Azure services.<br/> </p><p><br/></p><p>- Mentor and guide junior engineers and drive technical excellence within the data team.<br/><br/><b>Technical Skills & Requirements:</b><br/><br/>- Primary Skills: Azure, Databricks, ADF, PySpark, Python<br/><br/><b>Experience :</b><br/> </p><p><br/></p><p>1.
10+ years in Data Warehousing and ETL development<br/> </p><p><br/></p><p>2.
5+ years of hands-on experience with Azure Databricks<br/> </p><p><br/></p><p>3.
Strong working knowledge of Azure Data Factory and Azure Synapse<br/> </p><p><br/></p><p>4.
Proven expertise in data architecture, pipeline orchestration, and performance optimization.<br/><br/></p><p> 5.
Solid understanding of CI/CD practices, version control (Git), and cloud-native deployment pipelines</p><p></p><br/><br/></p> (ref:hirist.tech)