• Designed and optimized ETL workflows for efficient data transformation from diverse sources.• Developed scalable data lake architectures supporting structured and unstructured data.• Leveraged big data tools like Apache Hadoop and Spark for processing vast datasets.• Built a data warehouse to streamline data storage and retrieval processes.

outsource• Build flexible, extensible agile data schemas, focus on domain-based architecture aligned with business needs and eliminate data silos.• Partners with key stakeholders and proactively consults with project integration regarding architecture requirements and direction.• Apply methodology and governance, to minimize business and technical risks and adhere to quality assurance and data reconciliation. • Engage & coordinate with client’s teams in order to facilitate projects development, delivery, and support. • Lead reverse engineering exercise for legacy ETL and data management solutions• Understanding business problems to ensure projects are leveraging the appropriate technology and analytical tools in the delivery of a comprehensive solution• Understand the business goals while utilizing big data technology to ingest & analyze data streams.• ETL/ELT Data management, processing & EDA using: Python, IMPALA, Hive, SQL, PySpark, Pandas, Numpy, Query Grid, Sqoop, Airflow, zookeeper, Tableau, MS Power-BI, Yarn, Spark, Hadoop, SQL, DBeaver, Hue, Isilon, sentry and shell scripts.

The training program is launched by the Ministry of Communications and Information Technology (MCIT), provided by Amazon Web Services (AWS), and managed by the Information Industry Development Agency (ITIDA).The program targets building technical capacities in Artificial Intelligence (AI) and Machine Learning (ML), capitalizing on cloud computing that helps accelerate the implementation of AI and data analysis national projects

acquired skills:Node JS NLP using Wit.ai Platform deal with Botkit Platform