Data Engineer

GMK is a UK-based cloud based startup in UK focused on delivering scalable cloud solutions, and improving business efficiency through secure cloud services. .

• Designed and developed ETL architecture and Data Pipelines in Azure Cloud from scratch with Java, Python, and SQL, enabling efficient loading of operational data into the Data Warehouse and achieving a 99.9% accuracy rate for loaded data.
• Designed and implemented a comprehensive data cleansing framework using Python, and SQL, resulting in a 60% reduction in manual effort required for data cleaning.
• Built Azure Databricks notebooks and built business models using SQL, Python, and Java to provide business owners with greater visibility on terminal performance, enhancing decision-making processes.
• Collaborated exclusively with stakeholders from 5 departments to meticulously gather requirements, facilitating the design, construction, and execution of a spectrum of data platform initiatives.
• Pulled data from multiple sources, including Rest API, Kafka, SQL Server, Blob, Gen2, and Delta Lake, using ADF, Databricks, and Java.

Data Engineer

Bank of America is a global financial institution offering a wide range of banking and investment services. It focuses on innovative digital solutions and personalized customer experiences.

• Worked exclusively with stakeholders across 6 departments to gather requirements, design, build, and execute various data platform initiatives.
• Engineered multiple data pipelines using Databricks and Azure Data Factory (ADF), extracting data from over 10 structured and unstructured sources. Additionally, created triggers to automate Data Factory pipelines and Dataflows.
• Orchestrated seamless data ingestion and storage across multiple sources into Azure Data Lake Storage (ADLS) Gen2, amplifying data accessibility by 30%.
• Extracted business and finance data from various sources, including Azure SQL, Snowflake, Amazon Redshift, on-premises SQL Servers, and various web applications, and staged it in ADLS Gen2 using Azure Data Factory (ADF) pipelines.
• Assisted more than 100 end users in troubleshooting data-related issues, performance issues, resolving queries, and ensuring the smooth functioning of BI Solutions.
• Developed Power BI reports to analyze business trends, improving decision-making efficiency by 20% and increasing quarterly sales by 15%.

Data Engineer

Accenture, a global leader in consulting, technology, and outsourcing with a focus on digital transformation. Employs 600,000+.

• Collaborated with stakeholders from various departments, including business users, IT teams, and executives to understand data requirements and translate them into 10+ business dashboards.
• Created and implemented an ETL pipeline using Azure Databricks and Data Factory to automatically extract data from various sources and prepare it for reporting teams by cleaning data, denormalizing, and organizing it.
• Led the successful migration of complex company data from on-premise to cloud using Databricks and Azure Synapse, leading to a 25% increase in performance.
• Established frameworks for data governance to guarantee the appropriate management, security, and privacy of data.
• Updated current dashboards, reports, and dataflows while focusing on ad hoc tasks to enhance such reports.
• Provided technical support to internal teams in troubleshooting and resolving 300+ data-related difficulties.

Data Analyst Intern

Claro, a cloud based data-driven solution based company and mainly it offers services like Cloud infrastructure services, PaaS, SaaS. And has 1000+ employeees.

• Worked with and interpreted diverse client finance and sales datasets to identify trends and insights.
• Delivered bi-monthly reports to upper management, providing strategic insights for decision-making, and presented clear data insights to business stakeholders.
• Using Power BI, generated 15+ story-telling dashboards that deliver actionable insights into operational efficiency.
• Published reports to Power BI Service, managed users and user groups, implemented Row-Level Security (RLS), and configured scheduled data refreshes using Gateways for on-premises data sources.

Masters in Data Science

Grade: First Class distinction

Bachelors in Computer Science

Grade: First class distinction.