Data Engineer

Responsibilities

• Design, build, and maintain scalable data pipelines using Databricks, Spark, and Python
• Develop and manage data transformation workflows using dbt
• Implement and maintain ETL/ELT processes using Azure Data Factory
• Work with SQL Server to manage, query, and optimize structured data
• Create data models and support data architecture initiatives
• Develop dashboards and reporting solutions using Power BI
• Integrate data from multiple sources ensuring consistency and quality
• Support legacy and reporting systems using SSIS and SSRS (preferred)

• 8+ years of experience as a Data Engineer
• Strong hands‑on experience with Databricks, Spark, and Python
• Solid experience in Azure Data Factory for data orchestration
• Proficiency in SQL Server and advanced SQL querying
• Experience working with dbt for data transformation
• Exposure to Power BI for reporting and visualization
• Familiarity with SSIS and SSRS (preferred)
• Strong understanding of data architecture and data modeling concepts

• Design efficient and scalable data pipelines and workflows
• Optimize performance of SQL queries and Spark jobs
• Handle large‑scale data processing and transformation
• Translate business requirements into technical data solutions
• Ensure data quality, integrity, and governance
• Work independently and manage multiple data engineering tasks
• Collaborate with cross‑functional teams for data‑driven solutions
• Troubleshoot and resolve data‑related issues effectively

• Opportunity to work on modern data engineering tools and technologies
• Exposure to Azure‑based data platforms and architecture
• A role focused on end‑to‑end data lifecycle management
• Hands‑on experience with Databricks, dbt, and Power BI ecosystems
• Challenging projects involving large‑scale data processing
• Collaborative environment working with data and analytics teams

Want to discuss this opportunity in more detail? Feel free to reach out.