Description

You will design and build scalable data pipelines on Azure to collect, process, and store large datasets.

This role is on-site.

Responsibilities

• Design and implement efficient data models, warehousing solutions, and ETL/ELT processes aligned with business requirements.
• Develop and optimize data pipelines for ingestion, transformation, and storage using Azure Data Factory and Databricks.
• Collaborate with data scientists and analysts to integrate data workflows and ensure seamless cross-functional delivery.
• Monitor operational health of data solutions, troubleshoot issues, and enforce data governance, compliance, and security standards.
• Document architecture, workflows, and best practices for data ingestion and transformation.

Required Skills

• 5+ years of experience in data engineering, data architecture, or related roles.
• Proficiency in SQL, T-SQL, Python, PySpark, Scala, or Java for data processing and scripting.
• Hands-on experience with Azure Data Services: Azure Data Factory, Azure Data Lake, Azure Databricks, and Azure Synapse Analytics.
• Strong understanding of data warehousing concepts, including star schema, data marts, and normalization/denormalization.
• Experience with Azure Blob Storage, Cosmos DB, and relational databases (Azure SQL Database, SQL Server).
• Familiarity with DevOps practices, CI/CD pipelines, and version control (Git).
• Knowledge of data visualization tools like Power BI and monitoring tools like Azure Monitor or Log Analytics.

Preferred Skills

• Experience with Infrastructure as Code (ARM templates, Terraform) and DataOps automation.
• Exposure to Azure AI & Machine Learning services.

Key Skills

Education

Any Gradute