
Lead Cloud Data Architect
7 days ago
Senior Data Engineer Position
Our company seeks a highly skilled Senior Data Engineer to join our team. As a key member, you will design and develop scalable data pipelines using Azure Data Factory and Azure Synapse Analytics.
Key Responsibilities:
- Data Pipeline Design and Development: Design and develop scalable data pipelines using Azure Data Factory and Azure Synapse Analytics.
- Lakehouse Architecture Building: Build and optimize lakehouse architectures on Azure using Delta Lake.
- Stakeholder Collaboration: Work closely with stakeholders to understand their requirements and translate them into technical scripts.
- Data Ingestion and Orchestration: Implement data ingestion, transformation, and orchestration workflows from diverse sources (APIs, databases, cloud storage).
- Data Quality Assurance: Ensure data quality, consistency, and security across the data lifecycle.
- Azure Service Utilization: Leverage Azure services such as Data Lake Storage Gen2, Event Hubs, Azure Functions, and Key Vault.
- Infrastructure as Code Implementation: Implement Infrastructure as Code (IaC) using Terraform or Bicep for automated provisioning and configuration.
- Cloud Resource Optimization: Optimize cloud resource usage for performance and cost-efficiency.
- Star Schema Design: Design and implement star schema and other data modeling techniques to support analytical workloads.
- Collaboration with Analysts: Collaborate with analysts and data scientists to deliver advanced analytics solutions.
Required Technical Skills:
- Azure Expertise: Expert-level experience with Azure Data Services: Azure Data Factory, Azure Databricks, Azure Synapse, Azure Data Lake Storage.
- SQL Proficiency: Strong proficiency in SQL for complex transformations and performance tuning.
- Python Skills: Advanced Python skills for data pipeline development and orchestration.
- Terraform Experience: Experience with Terraform or similar IaC tools for Azure.
- CI/CD Knowledge: Familiarity with CI/CD pipelines and DevOps practices.
Soft Skills & Mindset:
- Growth Mindset: Growth mindset with a passion for continuous learning and innovation.
- Collaboration Skills: Strong collaboration skills across engineering, analytics, and business teams.
- Client Management Skills: Robust client management skills.
- Structured Problem-Solving: Structured problem-solving approach with a focus on scalability and maintainability.
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