Data Engineer Power Bi
Resume:
• Azure Data Factory
(ADF)
• Databricks
• SSIS
• PySpark
• SQL
• Azure SQL DB
• CosmosDB
• ADLS
• Delta Lake
• S3
• Redshift
• Power BI
• Tableau
• SSRS
• SAP BO
• Microsoft Azure
• Azure Synapse
Analytics
• Azure Databricks
• Unity Catalog
• RBAC
• Data Encryption
• Airflow
• Azure Logic Apps
• Git
• Azure DevOps
A highly skilled and motivated Azure Data Engineer with over 4 years of experience in developing, implementing, and optimizing data solutions. Strong expertise in Azure services, ETL development, business intelligence, data warehousing, and cloud-based technologies. Proven ability to enhance data systems' performance, improve data processing pipelines, and generate actionable insights through advanced analytics. Proficient in designing scalable data storage solutions, integrating diverse data sources, and ensuring seamless data flow across platforms. Adept at working in collaborative environments and delivering high-quality results with a focus on performance optimization and business value.
Pranay
Technology Stack: Azure, ADF, Databricks, Synapse, Fabric, ADLS, Delta Lake, Dataverse, CRM, Azure SQL DB, Unity Catalog, Python, PySpark, SQL, Power BI, DevOps
Designed and implemented end-to-end ETL pipelines using Azure Data Factory (ADF), improving data processing speed by 30% and reducing manual interventions.
Optimized big data workflows in Databricks, cutting runtime by 40% through optimized Spark jobs and automation, leading to more efficient data transformation processes.
Built a scalable data lake architecture using ADLS, enhancing storage efficiency and reducing data retrieval time by 25%.
Integrated data from various sources, including CRM systems, into Azure Synapse, providing real-time data analytics and improving decision-making.
Utilized Unity Catalog and Delta Lake for data governance, ensuring proper lineage tracking and enhancing data reliability by 20%, improving data transparency, compliance, and trustworthiness across the organization.
Developed interactive Power BI dashboards, reducing report generation time by 35% and enabling business stakeholders to gain real-time insights into key metrics.
Created SQL-based models for report generation, simplifying data analysis and reducing query execution time by 25%.
Automated deployment processes using DevOps practices, resulting in faster deployment times and increasing pipeline reliability by 50%, ensuring smoother transitions and continuous integration across the development lifecycle.
Applied machine learning models in Databricks to improve business forecasting accuracy by 15%.
Collaborated closely with business users to define key performance indicators (KPIs), resulting in more effective tracking of business objectives.
Designed and implemented a real-time data pipeline using Azure Databricks and Synapse, enhancing analytics capabilities for faster decision-making.
Provided comprehensive documentation and training to stakeholders, ensuring smooth adoption and use of new data solutions.
PROFESSIONAL EXPERIENCE
WEX Inc. 10/2024 - Present
Data Developer
Data Engineer
************@****.***
UK
CONTACT
SKILLS
PROFILE SUMMARY
Data Engineer
Sai Rasi IT 08/2022 - 08/2024
Technology Stack: Azure, ADF, Databricks, Synapse, CosmosDB, ADLS, Delta Lake, Azure SQL DB, Unity Catalog, Python, PySpark, SQL, Power BI, DevOps, Airflow, S3, RedShift, CRM
Designed robust ETL pipelines using Azure Data Factory (ADF), reducing data processing time by 35% and increasing operational efficiency, automating complex data workflows across the enterprise.
Leveraged Databricks to process large datasets, optimizing the transformation layer and cutting data processing time by 40%, significantly enhancing data processing speed and resource utilization.
Integrated CosmosDB with Azure SQL DB for seamless data flow, improving data consistency and reducing data errors by 25%, ensuring reliable and accurate data for decision-making.
Implemented Delta Lake on ADLS to enable scalable and efficient data storage, improving data quality and processing speed by 30%, ensuring high-quality data storage and faster retrieval.
Designed Airflow-based data workflows to orchestrate complex pipeline tasks, resulting in improved scheduling and reliability of data jobs, streamlining task management and automation.
Automated data synchronization between Azure SQL DB and RedShift, optimizing the ETL process and reducing data transfer latency by 15%, improving real-time data access and performance.
Created interactive Power BI dashboards to visualize key business insights, reducing report generation time by 40%, allowing stakeholders to quickly derive actionable insights for decision-making.
Integrated data from various CRM systems into the data warehouse, enabling comprehensive customer insights and improving marketing strategies, providing a unified view of customer interactions.
Developed Python scripts to automate data cleaning processes, resulting in a 20% increase in data accuracy and consistency, improving data integrity and reliability across systems.
Applied machine learning models using Databricks to provide predictive analytics, enhancing business decision-making capabilities and enabling better forecasts for strategic planning.
Optimized data pipelines with Azure DevOps, reducing deployment time by 50% and increasing pipeline reliability, ensuring smoother and faster releases and updates to production environments.
Streamlined data storage and retrieval with S3, improving overall data accessibility and reducing storage costs by 10%, enhancing the efficiency of cloud storage management and data access. Client: Citi Bank, HP
Data Engineer & Analyst
CapGemini 02/2019 - 02/2020
Technology Stack: Azure, ADF, Databricks, SSIS, SSAS, SAP BW, SAP BO, ADLS, Delta Lake, Azure SQL DB, Python, PySpark, SQL, Power BI, Git
Developed ETL solutions using SSIS and ADF, improving data integration efficiency and reducing processing times by 30%, streamlining complex data workflows for faster results.
Integrated SAP BW with Azure Data Lake Storage (ADLS), enhancing data storage capabilities and making the data accessible for analysis in real-time, providing more agile data access for business insights.
Optimized the performance of Azure SQL DB by implementing indexing and partitioning strategies, resulting in a 25% improvement in query execution times, boosting database performance and query response rates, leading to faster data retrieval and improved user experience.
Implemented Delta Lake as a storage solution for large datasets, improving data processing reliability and reducing duplication errors by 20%, ensuring high-quality and consistent data for business analysis.
Built advanced reporting solutions in Power BI, reducing the time spent on generating reports by 35% and enhancing accessibility of critical data insights, enabling more efficient decision-making.
Leveraged SSAS to build multidimensional data models, reducing report generation time and providing powerful analytical tools for business users, improving business intelligence capabilities across teams.
Automated data cleansing and transformation processes using Python and PySpark, resulting in a 35% reduction in manual data processing efforts, increasing efficiency and data quality.
Created customized Power BI dashboards, enabling stakeholders to access real-time business insights and improving reporting capabilities, providing actionable insights that drive informed business decisions.
• Integrated various data sources, including SAP systems, into a centralized reporting solution, enabling more accurate and timely decision-making.
• Used Git for version control, ensuring the integrity of the code and improving collaboration across
Developed scalable data pipelines in Databricks, improving data throughput by 30% and reducing system downtime.
Defined data validation and testing processes, resulting in a 25% reduction in data errors and increasing confidence in business reports.
Client: DTE Energy
Data Engineer
CapGemini 10/2018 - 02/2019
Technology Stack: SSIS, SSRS, SSAS, Power BI, Tableau, Alteryx, SAP
Designed and implemented robust ETL processes using SSIS, improving data processing efficiency by 20% and ensuring data consistency, resulting in streamlined workflows and reliable data delivery.
Built interactive Power BI dashboards that enabled real-time business insights and reduced reporting time by 35%, providing stakeholders with quick, actionable information to drive better decisions.
Developed reporting solutions in SSRS, providing business stakeholders with accurate, comprehensive reports that improved decision-making, delivering clear and actionable insights for strategy planning.
Created data models in SSAS, resulting in faster report generation times and providing powerful analytical tools for business users, enabling more efficient data analysis and better decision-making.
Integrated SAP systems into the BI ecosystem, enabling seamless reporting and analysis of business- critical data, providing a unified view of business operations for improved reporting accuracy.
Leveraged Alteryx for data preparation and cleansing, significantly reducing manual intervention and improving data accuracy, ensuring that high-quality data is used in business intelligence processes.
Created visually appealing Tableau dashboards, which reduced the time required to interpret data and increased business insight by 40%, enabling quick access to key performance metrics for better decision-making, ultimately driving more efficient and informed actions across the business.
Optimized SSIS ETL packages, cutting load times by 25% and improving data processing speed and efficiency, resulting in faster and more reliable data flows across the system.
Collaborated with business teams to define custom reporting requirements, ensuring that BI solutions met the specific needs of each department, improving the relevance and impact of the data insights.
Integrated SAP data into Power BI, providing stakeholders with accurate, real-time insights into business operations, empowering teams with up-to-date information to act swiftly on business opportunities, improving responsiveness and strategic decision-making.
Automated data validation and transformation processes, improving data quality and reducing errors by 30%, ensuring clean and reliable data for accurate analysis and reporting.
Managed project timelines and ensured the on-time delivery of BI solutions, achieving a 95% client satisfaction rate, demonstrating strong project management and client-focused delivery. Education
• MSc Business with Financial Management with Advanced Practice Northumbria University - 2022
• Bachelor of Commerce
Krishna University – 2018
Certifications
Microsoft Certified: Azure Data Engineer Associate (DP-203)
Microsoft Azure Data Fundamentals (DP-900)
Microsoft Power BI Data Analyst (PL-300)
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