Data Engineering Architect
GlobalFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 11+ years
- Required Skills
- PythonSQLMicrosoft AzureMicrosoft SQL ServerJSONdbtDatabricksPySpark
Requirements
- 11+ years of professional experience in the Data & Analytics area.
- 5+ years of experience in the Senior Consultant role with a strong focus on Azure data solutions.
- Advanced knowledge of architecture, application design, systems engineering, and integration.
- Very good knowledge of cloud data services, data warehousing, big data technologies, and data lakes (especially Azure, Databricks).
- Expertise in data modeling, data integration, and ETL processes.
- Proven experience using Microsoft ETL tools (Azure Databricks, Azure Data Factory, Data Lake, SSIS).
- Experience with Databricks Unity Catalog, Asset Bundles, Data Factory, Microsoft Fabric, Logic App, Function App.
- Programming skills for data analysis (especially PySpark, SparkSQL, Python, SQL).
- Familiarity with data governance, data security, and compliance standards.
- Familiarity with agile methodologies and the ability to apply DevOps and DataOps principles.
- Ability to use ARM templates.
- Experience working with JSON.
- Good understanding of business processes and ability to drive automation.
Responsibilities
- Advise on designing data architectures in Microsoft Azure.
- Lead data integration efforts, including ETL processes.
- Leverage Azure, dbt, and Databricks for data pipelines and analytics.
- Advise on security and compliance standards in cloud environments.
- Monitor and optimize data solutions for cost-efficiency.
- Advise on data governance and quality standards.
- Work with cross-functional teams to provide data solutions.
- Mentor junior team members in cloud data architecture best practices.
- Implement data ingestion pipelines using Azure Data Factory, Azure Databricks, and other ETL tools.
- Develop scalable and re-usable frameworks for data ingestion and processing.
- Design, build, and manage SQL server databases in the Azure cloud.
- Perform data modeling and integrate data from various systems.
- Review and implement best practices for data manipulation.
- Create and support Azure Data Factory pipelines.
- Integrate end-to-end data pipelines ensuring data quality and consistency.
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