Description

Job Description

What you know

• Design, develop, and maintain scalable, high-performance data pipelines across Azure cloud platforms.
• Build and orchestrate ETL/ELT workflows using Azure Data Factory (ADF).
• Develop enterprise-grade data models (dimensional, relational, lakehouse) to support analytics and reporting needs.
• Implement and optimize data processing solutions using Azure Databricks and distributed computing frameworks.
• Support AI/ML initiatives by enabling curated datasets and workflow integration using Azure Machine Learning pipelines.
• Collaborate with data scientists, analysts, architects, and business stakeholders to deliver trusted data products.
• Ensure best practices in data governance, security, quality, and compliance across platforms.
• Monitor and optimize pipeline reliability, performance, and cost efficiency in production environments.
• Contribute to CI/CD automation and operational excellence for enterprise data workflows.

Important attributes for this role

• Strong data modeling mindset (enterprise, analytics, and lakehouse architectures)
• Ownership of end-to-end data architecture and delivery
• Ability to work cross-functionally with technical and business teams
• Clear communication and stakeholder alignment
• Strong decision-making in platform and architecture design
• Enterprise focus on reliability, security, and scalability

What you'll do

• 8–10 years of experience in Data Engineering, Data Platform Engineering, or related roles.
• Strong experience building cloud-scale data solutions in the Microsoft Azure ecosystem.
• Hands-on expertise with Azure Data Factory for orchestration and automation.
• Experience with Azure Databricks for large-scale data transformation and processing.
• Strong proficiency in SQL and Python for data engineering workflows.
• Experience working with Azure Data Lake Storage (ADLS) and modern lakehouse architectures.
• Familiarity with Azure Machine Learning pipelines and supporting feature/data workflows for ML teams.
• Strong understanding of data governance, lineage, and quality frameworks.
• Experience with Delta Lake and modern lakehouse design.
• Familiarity with DevOps practices, CI/CD pipelines, and Infrastructure-as-Code.
• Experience working in large-scale enterprise environments with complex data integration needs.
• Knowledge of Azure security best practices (RBAC, Key Vault, encryption).

Education

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (required).
• Master’s degree is a plus

Key Skills

Education

Any Graduate