Enthusiastic and insightful Azure Data Engineer with over nearly 2 years of IT experience, specializing in Data Engineering and Data Modelling Hands-on experience in Azure Cloud, Data Bricks, Data Lake, ADF, and reportin…
Enthusiastic and insightful Azure Data Engineer with over nearly 2 years of IT experience, specializing in Data Engineering and Data Modelling Hands-on experience in Azure Cloud, Data Bricks, Data Lake, ADF, and reporting tools like Power BI and Tableau Experienced in building and managing data lakes aggregating dozens of data sources and providing insights to multiple different stakeholders based on terabytes of data Successfully built and implemented a real-time data pipeline using Azure Data Lake and Data Bricks to analyze customer behavior and inform targeted marketing campaigns, resulting in a 30% increase in customer engagement Innovative in migrating data and databases from on-premises infrastructure to Azure Data Lake, using tools such as Azure Storage Bucket, Azure Functions, and Azure SQLDB Developed and maintained data ingestion pipelines using Azure Data Factory to extract, transform, and load structured Expert knowledge in different Azure Data architectures & technologies such as Azure Data Factory, Azure Databricks, Azure SQL, Azure Gen1 and Azure Gen 2 data lakes, and Delta Lake Proficient in Python programming language with expertise in data manipulation libraries like pandas, NumPy, and SciPy Well versed in configuring CICD pipelines resulted in efficient and seamless data deployments, enabling faster insights and enhanced decision-making capabilities Worked in an agile environment and have good insight into agile methodologies and Lean working techniques. Participated in Agile ceremonies and Scrum Meeting Exhibited strong communication skills and a keen understanding of project timelines and dependencies.
Designed and developed auto-mated transactional data processing pipelines using Logic Apps, Azure Functions, and other Azure components, improving efficiency and reducing manual work
Created interactive dashboards and reports to provide insights into key banking metrics, such as loan performance, credit risk, and customer behavior, aiding senior management in strategic decision-making
Created and maintained data models and KPI metrics in Power BI, Tableau, and other BI tools, designing and implementing data visualizations and dashboards to provide real-time insights to business stakeholders
Implemented data security measures to protect sensitive financial information, ensuring compliance with data protection regulations like GDPR or HIPAA as relevant to the banking sector
Managed and maintained data security and compliance using Azure Key Vaults and other Azure security services, ensuring data is protected from unauthorized access and meeting regulatory requirements
Designed and developed ETL pipelines using Azure Data Factory, Azure Data Lake, and other ETL tools to move and transform data from various sources to a centralized data repository, ensuring high reliability, scalability, and security
Developed data integration solutions to integrate a variety of data sets from disparate sources into a data model to support BI and analytical requirements, ensuring data is accurate and accessible for advanced analytics
Built a scalable data infrastructure using Azure cloud technologies, reducing infrastructure costs by 30% and improving data processing performance by 50%
Identified and mitigated data privacy risks, security, and quality risks
Worked on documenting databases, data process flows, and maintaining data dictionaries, metadata, and data lineage documentation to provide transparency and traceability of data assets
Built solutions on Azure cloud using technologies like Azure Data Factory, Azure Data bricks, and Azure SQL Server, leveraging cloud computing to increase scalability and reduce costs
Involved in developing and maintaining data ingestion pipelines using Apache Kafka, Azure Event Hubs, and Azure Data Factory, enabling real-time data streaming and processing
Designed and implemented end-to-end ETL pipelines using Azure Data Factory to efficiently extract, transform, and load data from various sources into Azure data storage solutions
Implemented data partitioning, indexing, and distribution strategies to improve data retrieval speed and overall system performance
Designed and developed data models using tools like Azure Data Lake Store and Azure SQL Database, ensuring efficient storage, retrieval, and analysis of structured and unstructured data
Implemented data cleansing and transformation processes to ensure data quality and consistency using tools like Azure Data Factory and Azure Data bricks
Leveraged Azure Stream Analytics to process and analyze real-time data streams, enabling timely insights and actions based on streaming data sources
Implemented security measures like Azure Active Directory integration, role-based access control, and encryption to safeguard sensitive data throughout the data lifecycle
Implemented anomaly detection algorithms to identify potential fraudulent activities within call records and transactions, safeguarding the company and its customers from fraudulent actions
Established monitoring and alerting systems using Azure Monitor and Application Insights to proactively identify and resolve performance bottlenecks and issues
Collaborated with cross-functional teams including data scientists, analysts, and developers to define data requirements and ensure seamless integration of data solutions
Managed end-to-end data engineering projects, including requirements gathering, planning, execution, and timely delivery within budget
Kept up-to-date with the latest Azure services, features, and best practices through self-learning, online courses, and certifications
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