Crop Picture
NOTE: Do not upload any image that violates our Picture Policy. Doing so will result in the removal of the concerned image without prior notification.
Summary
• 3.5 Years of experience working with Data domain in various roles including Data Engineer, Data Modeler, BI Analyst and Software Developer.
• Hands on experience in 1. Implementation of ERPs, Data warehousing projects with various Structured and unstructured data sources including Amazon Redshift, Postgres, MySQL, MongoDB, DB2 and Oracle 2. BI Reporting, 3. Data migrations.
• Good grasp on Data ETL pipelining using Numpy, Pandas using python and implementing various data science models and algorithms using Scikit-Learn.
• Strong background with many data related industries including banking, Telecom, E-Commerce and IOT.
• Experience of working in all roles from requirement engineering to delivery for ERP implementation and DWH projects.
• Experience with different open source tools including hive, presto, airflow, Pentaho Data Integration.
• Familiarity with technologies such as MEAN stack, LAMP stack, Java, .NET.
• Hands-on experience and usability knowledge of Mac, Linux and Windows OS environments.
• Bachelor’s in computer system engineering with a concentration in Software development and Databases.
• Good communication skills, good analytical & design skills, focused approach, team player, Adaptive, hardworking and professional attitude to work.
Projects
Experience
Sr. Software Engineer
Techlogix is an IT services, consulting and business solutions company that helps its global clientele achieve enterprise transformation by either implementing state of the art ERPs or help them migrate from old ones. I am working here as a data engineer. My job role includes interaction with various national and international clients, requirements understanding and design implementations, BI Reporting, Data pipelining, Building and designing dash boards for end users.
Major Responsibilities:-
• Getting Requirements from cross business multiple business areas and creation of Dashboards to facilitate the business needs.
• To design and maintain enterprise scale data Engineering stack and use it to perform day to day data engineering tasks.
• Extraction of data from heterogeneous sources, transformation of it to reporting needs of the business and Loading it to the data warehouse.
• Creation and maintenance of real time pipelines.
