Data Engineer (Infra/DevOps Focus)

We are looking for a highly skilled Azure Data Engineer with expert knowledge in cloud infrastructure and DevOps automation. This critical hybrid role will be responsible for designing, building, optimizing, and automating our entire end-to-end data platform within the Microsoft Azure ecosystem. The ideal candidate will ensure our data solutions are scalable, reliable, and deployed using modern Infrastructure as Code (IaC) and CI/CD practices.
Key Responsibilities
Data Platform Development & Engineering
Design & Implement ETL/ELT: Develop, optimize, and maintain scalable data pipelines using Python, SQL, and core Azure data services.
Azure Data Services Management: Architect and manage key Azure data components, including:
Data Lakes: Provisioning and structuring data within Azure Data Lake Storage (ADLS Gen2).
Data Processing: Implementing data transformation and analysis logic using Azure Data Factory (ADF), Azure Synapse Pipelines, and Azure Databricks (using Spark/PySpark).
Data Warehousing: Designing and optimizing the enterprise Data Warehouse in Azure Synapse Analytics (SQL Pool).
Data Modeling and Quality: Define and enforce data modeling standards and implement data quality checks within the pipelines.
Cloud Infrastructure & DevOps Automation
Infrastructure as Code (IaC): Design, manage, and provision all Azure data resources (ADLS, Synapse, ADF, Databricks Clusters) using Terraform or Azure Resource Manager (ARM) Templates/Bicep.
CI/CD Implementation: Build and maintain automated Continuous Integration/Continuous Deployment (CI/CD) pipelines for all code (data, infrastructure, and application) using Azure DevOps or GitHub Actions.
Containerization & Compute: Utilize Docker and manage deployment environments using Azure Kubernetes Service (AKS) or Azure Container Instances (ACI) when required for data applications.
Monitoring, Logging, & Security: Configure comprehensive monitoring and alerting using Azure Monitor and Log Analytics. Implement network security and access controls (RBAC) across the data platform.
Required Skills & Qualifications
Azure Cloud: Strong hands-on experience designing and deploying end-to-end data solutions specifically within the Azure ecosystem.
Programming: High proficiency in Python (including PySpark) and expert knowledge of SQL.
DevOps & IaC: Proven, production-level experience with Terraform (preferred) or ARM/Bicep for automating Azure infrastructure deployment.
CI/CD: Experience setting up CI/CD workflows using Azure DevOps Pipelines or GitHub Actions.
Data Tools: Deep working knowledge of Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Orchestration: Experience with workflow orchestration tools like Azure Data Factory or Apache Airflow.
Preferred Qualifications
Azure certifications such as Azure Data Engineer Associate (DP-203) or Azure DevOps Engineer Expert (AZ-400).
Familiarity with Data Governance tools such as Azure Purview.
Experience with real-time data ingestion using Azure Event Hubs or Azure Stream Analytics.