With over 9+ years of dedicated service in the realm of Big Data, I have established myself as a thought leader and a driving force in the transformation of data landscapes. My journey in the tech industry has been marked by a relentless pursuit of excellence, a deep passion for innovation, and a commitment to leveraging data as a strategic asset. As a Big Data Engineer, I have been at the forefront of designing and implementing next-generation analytics platforms that are not only scalable and robust but also deliver actionable insights. My expertise in data gathering, modeling, analysis, validation, and architectural design has enabled me to create solutions that are not only optimized for performance but also aligned with business objectives. My professional experience is a testament to my versatility and adaptability. I have worked across various domains, from finance to healthcare, and from e-commerce to entertainment, My approach to data engineering is holistic. I believe in the power of data to tell a story, and my work in data analysis applications, batch processing, and real-time data architectures is a reflection of this belief. I am adept at using programming languages such as Java, Python, and Scala to bring these stories to life, and my experience with scheduling tools like Oozie, Airflow, and Azkaban ensures that these stories are told efficiently and effectively. Collaboration is at the core of my work ethic. I have worked in diverse teams, fostering an environment of trust, respect, and knowledge-sharing. My ability to communicate complex technical concepts to non-technical stakeholders has been instrumental in bridging the gap between data and decision-making. Technical Expertise: Big Data Technologies: Hadoop, Spark, Kafka, ELK, Hive, Pig, Sqoop, Zeppelin Programming Languages: Java, Python, Scala, Shell Scripting Scheduling Tools: Oozie, Airflow, Azkaban, Control-M Databases: MySQL, Oracle, Netezza, MongoDB Cloud Platforms: AWS, GCP, Azure, DataBricks CI/CD Tools: Git, Jenkins, BitBucket, Gerrit Data Processing: Data ingestion, Data integration, Data warehousing, Data analysis Data Governance: Data quality, Data compliance, Data security Agile Methodologies: Scrum, Kanban, Continuous Integration, Continuous Deployment