Mansi Singhal

Role & Responsibilities:

· Responsible for business understanding for a Retail client, Managing Various datasources Validation and Modelling them to a final flat table ready to be used for visualization purpose (Quarterly refresh for data sources)

· Managing a team of three graph developers by providing them the required functional understanding for code implementation.

Mentored cross team junior consultants as well, helping them enhance their skills and contribute more effectively to projects.

Built strong relationships with clients through consistent communication and proactive problem-solving efforts.

Identified any scope of project opportunity by pitching actively in the Client Interactions.

Major Technologies Worked on:

· Programming Languages: Python, SQL, DAX(Basics)

· Apache Spark

o Data Processing: Narrow & Wide transformations, UDFs, Schema Objects & Evolution.

o Optimization Techniques: Broadcast Joins, SMB Joins, Caching, Partitioning & Bucketing AQE, Caching.

o Memory Management: DAG Visualization, Memory usage while job execution.

· Azure Databricks

o Azure Databricks Workspace: Databricks Utilities, DBFS, Creating Mount Points.

o Delta Lake: Managing Delta Tables, Delta Logs, Optimization Commands for delta lake.

· SQL Server & Big Query

o SQL Analytical Queries using advanced window functions.

· Power BI & Advanced Excel

o Data Modelling & Validation

o Power Query, DAX.

►Handled the Oracle Argus database for the clients.

►Transformation and Manipulation of data using Power Query and performing analysis using DAX queries.

►Experience in Experience in the data analysis and providing solutions using Cognos 10.x and Cognos 11 reporting.

►Have worked over the Finance, Regulatory, Monthly MIS, Risk Reports and managed their metadata structured packages.

►Managed the different ETL workflows and jobs.

►Conceptualised and deployed a dashboard showcasing the LTD, MTD data for Cost , Revenue and the Forecasts.

►Participated in different Process improvements activities for every audit in the year.