Data Analyst
About Candidate
The candidate is an experienced Senior BI & Data Quality Analyst with a diverse background in data management, analytics, and reporting across various industries. Their expertise lies in developing and optimizing data workflows, ensuring data quality, and delivering actionable insights through advanced reporting tools.
In their current role, the candidate is responsible for managing data quality and driving improvements through the use of Databricks, Power BI, and Azure technologies. They contribute to international teams focused on data quality management, improving processes, and ensuring the timely and accurate delivery of data insights. They are adept at managing ETL workflows using tools such as Knime and Talend to streamline data processing and reporting. Previously, as a Data Analyst in the healthcare sector, the candidate improved operational efficiency by enhancing information systems and creating real-time dashboards. Their technical proficiency includes the development of log retrieval connectors and integration of automated solutions to monitor and analyze data.As a Consultant Data Engineer at ARKEA, the candidate was instrumental in designing and structuring large-scale data environments for Big Data processing, automating data processes with SHELL scripts, and ensuring data integrity through rigorous unit testing and version control. They also gained extensive experience in managing and deploying data workflows in Hadoop and Oracle environments.
In earlier roles, the candidate developed ETL pipelines, designed relational database models, and worked on the migration of NoSQL databases to structured formats. Their ability to model and build data warehouses, combined with strong skills in Power BI and Pentaho, has allowed them to deliver client-specific reports and dashboards. Throughout their career, the candidate has demonstrated a commitment to leveraging cutting-edge technologies such as Hadoop, Pig, Hive, Power BI, and SQL Server to enhance business intelligence capabilities. They have also shown expertise in Agile methodology, contributing to the development of scalable and efficient data solutions in collaborative environments.Technologies: Power BI, Azure, Databricks, SAP, Oracle, Knime, Python, Talend, SQL Server, Hadoop, Pig, Hive, SSIS, Pentaho, MongoDB, SpringBoot, Postgres, Angular, Docker.