Sukhjinder Singh Email & Phone Number

Sacramento, Ca, Us

Redmond, Washington, Us

• involved in the snowflake implementation and used various objects like snowflake Streams,Tasks,Shares. • Worked on DBT ( ELT tool) connection setup with Snowflake and have used DBT cloud to execute ELT pipelines in Snowflake. • Implemented Snowflake Continuous Data Loading, Snowflake Time Travel & Fail-safe and secured Data Sharing. • Define virtual warehouse sizing for Snowflake for different type of workloads. • Created streams on top of staging/Satellite tables for the change data capture. • Scheduled the tasks to trigger every min, once the stream captures the data from the staging table. • Develop stored procedures/views in Snowflake to load data into HUB and Satellite tables and the consumption Mart. • Worked on the DBT to connect snowflake DB and create the models to transform the data. • Worked on the swagger API UI to create the workflow creation/Extract to trigger automatically once the data loads are completed/validation completes. • Involved in Using the AZURE COSMO DB to unload the snowflake data,store the event log information in the log tables and the meta config info for the workflow related objects. • Used COPY to bulk load the data. • Created data sharing between two snowflake accounts. • Created internal and external stage and transformed data during load. • Redesigned the Views in snowflake to increase the performance. • Unit tested the data between PNA/GPA/AIS and Snowflake. • Good working knowledge of any ETL tool (ESP, SNOWFLAKE). • Validating the data from PNA to Snowflake to make sure it has Apple to Apple match. • Consulting on Snowflake Data Platform Solution Architecture, Design, Development and deployment focused to bring the data driven culture across the enterprises

Boulogne-Billancourt, Île-De-France, Fr

● Developed intricate algorithms based on deep-dive statistical analysis and predictive datamodeling that were used to deepen relationships, strengthen longevity and personalizeinteractions with customers.● Analyzed and processed complex data sets using advanced querying, visualization andanalytics tools.● Using the clustering algorithm (K-Means) for finding the similar devices in a station and findthe bad measurement for tuning the state estimator.● Built a predictive model to predict the likelihood that bad measurement based on weather,emergency as well as fire which result in 40 % influences.

● Utilized numerous statistical techniques, including sensitivity analysis on non-linearpropagation of errors, Markov-Chain Monte Carlo for model building,hyperparameter tuningand hypothesis testing via information criterion.● Research on smart meter power forecasting deep learning on a large dataset (15billions+).Constructed data processing pipelines including data cleaning, feature engineering, modelselection, training and evaluation.○ Building deep learning regression models on smart meter data achieve to forecastenergy demand to use energy most efficiently and save energy losses.○ Build Multi-class classifier models based on ML and DL algo’s including logisticregression, SVM, KNN, Decision tree, boosting, text mining, and Random forest toclassify which plan fitbest based on their energy behaviour.

• Applied breadth of knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop). • Migrated data from Heterogeneous Data Sources and legacy system (DB2, Access, Excel) to centralized SQL Server databases using SQL Server Integration Services (SSIS). • Applied Descriptive statistics and Inferential Statistics on varies data attributes using SPSS to draw insights of data regarding providing products and services for patients.

Master'S Degree, Data Science

Bachelor'S Degree, Computer Science