Data Engineer

Overview

Design and build scalable data pipelines, analytics solutions, and data models using Azure services to support governance, security, performance, and decision-making. Work with scientists, analysts, and stakeholders and contribute to analytics and machine learning development.

What you'll do

• Design and implement scalable data pipelines and analytics solutions using Azure services.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
• Develop and maintain data models, ETL processes, and data integration workflows.
• Ensure data quality, governance, and security across analytics platforms.
• Create interactive dashboards and visualizations for business decision-making.
• Optimize performance of data systems and troubleshoot issues as needed.

What you'll need

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
• 4-6 years of experience in data engineering.
• Hands-on experience with Databricks, Spark, and Microsoft SQL.
• Experience with data governance and security frameworks across Databricks and EDW ecosystems (access controls, data lineage, auditability, secure sharing).
• Experience with Azure Data Factory for orchestrating data workflows.
• Proficiency in Microsoft SQL Server for data storage and querying.
• Hands-on experience with Azure Data Lake for big data storage and analytics.

Nice to have

• Experience with enterprise applications such as SAP, Salesforce, Workday, or Adaptive Planning.
• Experience with Generative AI tools such as Azure OpenAI or Databricks Genie.
• Experience with version-control systems such as GitHub.

Details

• Technical skills include Azure Data Factory, Azure Databricks, Azure Data Lake Storage, and Azure SQL.
• Also includes SQL, Python, ETL development, and data warehousing.