I am a Lead Data Engineer with comprehensive experience in the development of Big Data systems for the provision of a Unified Analytics Platform (Batch & Streaming platforms). I am responsible for transforming data into informative insights and assisting the company in making data-driven choices, and I have expertise in developing and executing data pipelines. My experience spans the Health, Insurance, Finance, Reverse Logistics,  and  FMCG sectors  of the  economy. Key Qualifications: • Creating Big Data ETL Pipelines • Refine the data lake in preparation for business reporting. • Establishing a Unified Analytics Platform • Consider Design Thinking. • Improve the job execution time. • Strategy Development and Implementation • Communication Technologies: • MongoDB, Microsoft Azure, Spark, Python, Azure Data Lake Gen2, Azure Databricks, Azure Data Factory, Kafka, Spark Streaming, REST APIs, Snowflake, Django, Google Cloud Plateform • HDFS, SQOOP, Hive, GitLab, Azure Datawarehouse, Scala, Bitbucket, Jenkins, Agile Key accomplishments: • Job execution time was reduced from 8 hours to 2 hours. • Proactively designing and implementing the Job Failure Message User Story, which reduced roughly 70% of the debugging time required to investigate the failure. • Technical writer for freeCodeCamp, PlumbersofDatascience, and Towards Data Science on Big Data Internal Working and Optimizations on Medium. • Worked on optimising the performance of the Spark-based Data Integration framework utilising best practises, resulting in a 40% performance boost. • English fluency