Data Engineer (Azure&Databricks)

• Lead technical decisions for enterprise data architecture using Databricks
• Develop strategies for cost-effective, high-performance data architectures, covering
everything from data streams to analytical storage
• Design and implement data solutions in Microsoft Azure, based on project needs
• Build and maintain ETL processes and data models for analytical pipelines, especially in
Finance
• Establish and uphold best practices for software development, like version control,
testing, and CI
• Support pre-sales activities, including RFPs, proposals, and client communications
• Guide discussions on cloud data warehousing and machine learning platforms
• Provide technical support for vendor and third-party engagements
• Offer ongoing support for business and technology teams on platform strategy and
quality assurance

Elvárások:

• Bachelor’s degree in Computer Science, IT, or a related field
• Minimum 2 years of Databricks and 4 years of Azure experience (certifications preferred)
• Experience as a Data Architect/Engineer with hands-on expertise in Data Lakehouse,
Data Lake, and Data Warehouse design
• Strong knowledge of Databricks, Data Lakes and Spark
• Strong experience with Azure Platform Services (Identities, Network, Storage)
• Proficiency with Azure Data Services, including Azure Data Factory, Azure SQL
• Experience with streaming data technologies like Databricks Streaming, Kafka, Azure
Streaming Services
• Experience with Azure DevOps especially Azure Pipelines
• Proficiency in Python, PySpark, SQL
• Familiarity with DataOps

Nice to Have
• Deliver cloud infrastructure solutions using Infrastructure-as-Code
• Knowledge in Microsoft Fabric Ecosystem and PowerBi
• Knowledge of Azure infrastructure and security, Docker, and Kubernetes
• Experience with Apache Airflow
• Experience with open-source databases (e.g., Postgres, MySQL)

Egyéb információ az állásról:

We are seeking a Data Engineer to design and implement data solutions in Microsoft Azure. As a
Data Engineer, you will operate within some of our most versatile and complex client
environments, utilizing technologies such as ETL tools, SQL and Python.