Senior Data Engineer 📊 Senior Data Engineer | AWS Certified | Big Data & Cloud Solutions | Real-Time Data Platforms With over 5 years of experience in data engineering, I specialize in building robust, scalable, and distributed data pipelines tailored for real-time analytics, competitive intelligence, and dynamic pricing platforms. My expertise centers around architecting reliable data ecosystems and optimizing data workflows using a range of technologies including Apache Spark, Hive, Sqoop, Cassandra, and cloud platforms like AWS and Azure. As an AWS Certified Data Engineer, I’m well-versed with AWS services such as S3, Glue, EMR, Lambda, Athena, RDS, and Redshift, and I frequently leverage Databricks for large-scale processing. My core programming strengths include PySpark, SQL, and working knowledge of Scala in Spark environments. In past roles, I led initiatives to design and build modern data lakes and streaming data architectures, enabling unified 360-degree customer views that directly supported business functions such as sales, marketing, and analytics. My experience spans across technologies like Hadoop, MapReduce, HBase, Python, Kafka, Linux, Apache Airflow, and end-to-end ETL pipeline orchestration, along with foundational skills in Snowflake and Azure services. Holding a B.Tech in Electronics Engineering, I’m deeply committed to staying current with evolving tech trends and building data-driven solutions that address complex business needs. 🛠️ Technical Skills Cloud Platforms: AWS (S3, Glue, Lambda, EMR, Athena, DMS, Redshift, RDS, CloudWatch, IAM), Azure (Foundational) Languages & Tools: Python, PySpark, SQL, Scala (Intermediate), Hive, Sqoop, Cassandra, HBase, Databricks Data Engineering Tools: Apache Spark, Hadoop, Kafka, Airflow, HDFS ✅ Key Achievements Decreased ETL execution time by 40%, significantly enhancing reporting turnaround and enabling near real-time dashboards. Enabled seamless migration of large volumes of transactional data from on-premise systems to Amazon S3 via AWS DMS. Engineered end-to-end ETL solutions using AWS Glue and PySpark for efficient transformation and Redshift loading. Let me know if you'd like this tailored for a resume, LinkedIn profile, or portfolio introduction.