Data Engineer Sample Resume

• Designed and developed a new generic function-based framework for data processing using Databricks, SQL, Azure Data Factory, and Azure Functions.
• Created fully parameterized ADF pipelines and configuration databases to drive entire flow and logging logic.
• Developed PySpark scripts including generic functions, business custom functions, and master notebook execution functions.
• Implemented Azure functions to trigger and manage data processing workflows.
• Developed SQL stored procedures for logging activities and maintaining data integrity.
• Supervised and mentored team members to enhance their development skills.

• Designed and built new generic frameworks for processing data in retail and FMCG projects using Databricks and PySpark.
• Created PySpark classes, including Databricks Autoloader generic class, incremental loads class, and ETL classes.
• Implemented Great Expectations for data validation and quality assurance.
• Designed logging and configuration layers to streamline data workflows.
• Developed and managed Databricks workflows for efficient data processing.
• Collaborated with cross-functional teams to meet project requirements and deadlines.
• Provided technical support and troubleshooting for data processing issues.

• Rewrote solutions to make data processing frameworks more generic and scalable.
• Created frameworks using Databricks and Data Factory to process incremental data for external vendors and machine learning applications.
• Optimized old measures and data models in Azure Analysis Services (AAS), reducing data size significantly.
• Incorporated new data sources into the main data integration framework.
• Developed new components and enhanced existing ones for data integration processes.
• Conducted performance tuning and optimization of data processing workflows.

• Developed automated, event-based solutions for producing Power BI reports using Azure stack (Azure Data Factory, Logic Apps, SQL Service).
• Created new Power BI reports and supported performance improvements for existing ones.
• Designed and implemented data pipelines to integrate various data sources.
• Collaborated with stakeholders to gather requirements and deliver data solutions.
• Ensured data accuracy and consistency across all reports.

• Conducted end-to-end learning and development programs for employees.
• Built and analyzed HR reports using Power BI to support decision-making.
• Designed and delivered soft skill training programs.
• Developed and implemented HR policies and procedures.
• Collaborated with HR teams to improve employee engagement and retention.