Professional Summary
SKILLS O Jessica Claire Having over 7 years of experience as a Big Data and cloud Engineer with expertise in designing data- intensive applications using the Hadoop Ecosystem, Big Data, Cloud Data Engineering, Data Warehouse/ Data Mart, Data Visualization, and Reporting. Experience in implementing E2E solutions on Big Data using the Hadoop framework, executed, and designed big data solutions on multiple distribution systems like Cloudera (CDH3 & CDH4), and Hortonworks. Expertise in Big Data processing using Hadoop, Hadoop Ecosystem (Map Reduce, Pig, Spark, Scala, Hive, Sqoop, Flume and HBase, Cassandra, Mongo DB, Kafka Framework, Zookeeper and Oozie, Storm) implementation, maintenance, ETL and Big Data analysis operations. Adept in programming languages like Scala, and Apache Spark, including Big Data technologies like Hadoop, Hive, HBase, Sqoop, Oozie, and Zookeeper. Worked on analyzing data using SQL, Hive, and Spark SQL for Data Mining, Data Cleansing. Extensively used Python Libraries PySpark, Pytest, Pymongo, Oracle, PyExcel, Boto3, Psycopg, embedPy, NumPy, Pandas, Star base, Tabulae, matplotlib, and Beautiful Soup. Experience in developing data pipelines using AWS services including EC2, S3, Redshift, Glue, Lambda functions, Step functions, CloudWatch, SNS, DynamoDB, and SQS. Designed. Developed and implemented ETL processes using IICS Data integration. Experience in collecting real-time streaming data and creating the pipeline for row data from different sources using Kafka and storing data into HDFS and NoSQL using Spark. Have good knowledge and experience in Google Cloud Platform (GCP). Extensive experience with SQL in designing database objects such as Tables, functions, procedures, triggers, Views, and CTEs. Experience in Migrating SQL database to Azure Data Lake, Azure data lake Analytics, Azure SQL Database, Databricks, and Azure SQL Data Warehouse and Controlling and granting database access and Migrating On-premises databases to Azure Data Lake store using Azure Data Factory. Experience in creating Impala views on hive tables for fast access to data. Experienced in Erwin data Modeling iterations (Schematic/ Logical/ Physical) Forward and reverse-engineering processes. Proficient knowledge and hands-on experience in writing shell scripts in Linux. Experience in developing MapReduce jobs for data cleaning and data manipulation as required for the business. Used hive extensively to perform various data analytics required by business teams. Good experience in Tableau for Data Visualization and analysis on large data sets, drawing various conclusions. Experience in writing code in Python to manipulate data for data loads, extracts, statistical analysis, modeling, and data munging. Utilized Kubernetes and Docker for the runtime environment for the CI/CD system to build, test, and deploy. Experience in working on creating and running docker images with multiple microservices. Experience with ETL tools like Informatica, DataStage, and Snowflake. Well-experienced in Normalization and De-Normalization techniques for optimum performance in relational and dimensional database environments. Created Snowflake Schemas by normalizing the dimension tables as appropriate and creating a Sub Dimension named Demographic as a subset to the Customer Dimension. Cloud Ecosystem: Office Suite Data Analytics Warehouse Models SAN Technologies SQL Transactional Replications AWS Azure GCP