Mamtha Loknath

• Skilled Data Engineer with 5+ years of experience architecting, building, and optimizing large-scale data processing systems. Proficient in diverse programming languages, including Python and Scala Skilled in leveraging big data technologies such as Hadoop, Apache Spark, and Kafka for efficient data processing and streaming. • Expertise in data integration and ETL processes using AWS Glue, Informatica, and SSIS. Hands-on experience with cloud platforms, including AWS, and proficient in services like Lambda, S3, EMR, and RDS. • Experience in Data Engineering, Data Analysis/Business analysis, ETL Development, and Project Management. • Experience in Data transformation, Data mapping from source to target database schema, Data Cleansing procedures. • In-depth Knowledge of Hadoop Architecture and its components such as HDFS, Yarn, Resource Manager, Node Manager, Job History Server, Job Tracker, Task Tracker, Name Node, Data Node, and MapReduce • Adept in programming languages like Scala and Python including Big Data technologies like Hadoop, Hive • Developed highly optimized Spark applications to perform various data cleansing, validation, transformation, and summarization activities according to the requirement. • Developed Spark Structured Streaming & Batch applications for various business use-cases utilizing various programming languages such as Java, Scala & Python • Deployment: Experience in CI/CD tools like Jenkins, Bitbucket, Ansible, Maven, Ant, Git, SVN. • AWS: Experienced in deploying applications on AWS EMR, Glue, SNS, API Gateway, S3, Cloud watch, EC2, Lambda, Step functions, Athena, DynamoDB, Service catalogue, Glue , Redshift. • Experienced with efficient data warehousing environments like Redshift. • Developed the data ingestion tool with Spark-Scala, Py-spark and python scripts. • Experienced in application development for Insurance, Telecommunications & Financial domains. • Proven track record in designing and managing Snowflake and Amazon Redshift data warehouses, ensuring seamless data storage and retrieval. Extensive knowledge of databases, including MySQL, MongoDB, DynamoDB and Oracle. Proficient in real-time data streaming with AWS Kinesis and Apache Kafka. • Adept at Infrastructure as Code using Terraform, strongly focusing on automation and scalability. Skilled in data processing tools such as Pandas, NumPy, PySpark, and Apache Airflow. Experienced in containerization and orchestration with Docker and Kubernetes. • Strong background in monitoring and logging using CloudWatch and Splunk. Proficient in visualization and BI tools such as Tableau and Power BI, translating complex data sets into insightful visualizations. Well-versed in DevOps practices, utilizing Git, GitHub and Maven for version control and continuous integration. • Collaborative team player experienced in Agile and Scrum methodologies, ensuring efficient project delivery through clear communication and effective task management using JIRA.