Jafar Shaik — Data Engineer

• With over 3+ years of hands-on experience in Data Engineering, Analysis, and Modeling, I have developed a robust skill set in designing and optimizing data pipelines, extracting meaningful insights from complex datasets, and building efficient data models to drive business intelligence and decision-making. • Skilled in sourcing, validating, and transforming data from multiple systems into Azure Data Lake and Azure SQL Database using Python and SQL. • Hands-on experience designing and deploying scalable Azure Data Pipelines and utilizing Synapse for solving complex business problems related to large-scale data warehousing, analytics, and reporting. • Proficient in Python, T-SQL, Azure Data Factory, Exploratory Data Analysis (EDA), and creating insightful visualizations with Power BI. • Experienced in automating pipeline workflows, setting up triggers, and mapping data flows in Azure Data Factory (V2), while securely managing credentials with Azure Key Vault • Proficient in using Terraform for deploying, updating, and deleting multiple resources in Azure and migrating on-premises resources to the cloud • Worked in Agile development teams, demonstrating excellent communication skills, understanding of project timelines, and the ability to manage dependencies. Highly collaborative, self-motivated, and dedicated to ensuring successful project delivery. • Proficient in creating notebooks in Databricks utilizing PySpark and SQL for data extraction, transformation, and aggregation from multiple file formats. This process enabled deeper insights into client usage patterns by analyzing and transforming the data. • Developed automated ETL pipelines to streamline data ingestion, cleansing, transformation, and mapping processes, ensuring efficient and timely delivery of data to clients • Led the design and implementation of data engineering solutions, including data architecture, modeling, ETL development, automation, and migration for structured and semi-structured data, aimed at supporting data analytics products • Partnered with stakeholders to ensure adherence to best practices in data engineering, focusing on performance, reusability, and compliance with enterprise-wide data governance policies • Led the migration of data and databases from on-premises infrastructure to the Azure Data Lake and this involved transferring raw data to Azure Storage, processing it through Azure Functions and Azure Databricks, using HDInsight, and storing the results in Azure SQL Database and Azure Synapse

Stackforce AI infers this person is a Data Engineer specializing in Azure solutions for SaaS applications.

Location: Greater Toronto Area, Canada

Experience: 4 yrs 1 mo