Samuel

Samuel is a highly skilled data engineer with 6 years of experience. He excels in designing and implementing data pipelines, driving data-driven insights, and automating advanced analytics solutions. Samuel's expertise includes Azure Synapse Workspaces, SQL Server, SAP HANA, and Python scripting. He is proficient in data warehousing, ETL documentation, and utilizing analytics tools like Power BI. With a strong background in machine learning and .NET technology, Samuel delivers efficient data solutions and possesses in-depth knowledge of MongoDB for data storage and retrieval.

• Extensive experience in delivering complex and impactful data engineering projects across diverse industries, including direct sales, banking, trading, content services, retail, and services. Notably, contributed to the creation and deployment of pipelines for Azure Synapse, while actively participating in the creation and configuration of Azure subscription environments. Additionally, it played a key role in the creation of pipelines for seamless ingestion of data from the data warehouse to the data lake, ensuring efficient data flow and transformation. Also, successfully automated Azure ML models using out-of-the-box API consumption and training endpoints.

• Proficiency in designing and developing robust data architectures, pipelines, and data lakes, leveraging cutting-edge technologies and cloud platforms, particularly Azure Synapse Workspaces.

• Extensive expertise in working with diverse data technologies, including SQL Server, SAP HANA, Cosmos DB, Azure SQL, and Azure Synapse, enabling the efficient storage, management, and processing of data in large-scale enterprise environments. Notably, proposed a standard approach for recording real-time progress of processes in a SQL table, providing comprehensive monitoring capabilities.

• Proven track record of driving data-driven insights and business outcomes through advanced analytics solutions and automation, utilizing Microsoft cloud services. By implementing advanced analytics solutions and automating predictive processes using Microsoft cloud services, empowered organizations to make informed decisions and drive growth.

• Demonstrated expertise in various programming languages, such as Scala. Specifically, developed batch processes in Scala to handle the processing of master data for foreign customers. Python is also a notable area of expertise, as demonstrated by the development of a Python script to process invoice text data within a notebook environment. Proficient in data warehousing, ETL documentation from data sources, legacy ETL processes, and working with streaming, data vaulting, and analytics tools such as Power BI. Developed Power BI dashboards for managers, enabling comprehensive data visualization and analysis.

• Showed proficiency in machine learning, exemplified by the automation of Azure ML models using out-of-the-box API consumption and training endpoints, resulting in the delivery of comprehensive data solutions.

• knowledgeable in utilizing .NET technology for efficient development and implementation. Additionally, well-versed in working with MongoDB, a popular NoSQL database, to handle diverse data storage and retrieval requirements.

Tech Skills : 

Azure Synapse Workspaces

SQL Server

SAP HANA

Cosmos DB

Azure SQL

Scala

Python

Power BI

Azure ML

.NET technology

MongoDB