Arpit Gothwal

• Building ETL pipelines using Azure Data Factory and Azure Syanpse. • Integration of different data sources, design and implementation of data models for efficient data processing. • Implement CI/CD pipelines in Azure DevOps.

Projects: • Migration of Tableau Prep Flows to AWS Glue PySpark Jobs (Material Science): Utilized SDFL Architect of AWS, fetched data from S3 via glue, cleaned and transformed the data according to prep flow in PySpark and load the Sink as Athena table. • Migration of Qlik applications to Snowflake (Energy): Analysed Qlik Script, converted them to Snowflake SQL and supported creating Dashboards in Tableau.

Projects: • HR Data ETL Pipeline in AWS (Automotive Manufacturer): Created ETL Pipeline to fetch from S3 data lake, cleaned the data using PySpark including hashing to anonymized personal details, load the Sink to Redshift and build KPI Dashboard in Tableau. • KPI Dashboard in Tableau (Automotive Manufacturer): Transformed the data utilizing PySpark and Pandas, build Management KPI dashboard in Tableau. • SAP HANA (Life Science, Pharma): Wrote SQL Script to transform data.

• Conducting workshops with different stakeholders to identify required features for model training. • Cleaned and analysed data using pandas in python and developed a machine learning model with help of scikit-learn to identify customer as a family. • Visualized end results in Power BI and documented findings.

• Quality assurance and error analysis of manufactured Porsche models. • Building the visualization Dashboard and evaluation of the audit data of the vehicles.