saad arbani

Data Analyst

Mumbai, Maharashtra 7+ yrs exp 80 · Excellent

About

No bio added yet

Skills & Expertise (52)

SQL Advanced

9.0/10

Years Exp

Python Advanced

9.0/10

Years Exp

Google BigQuery Advanced

8.5/10

Years Exp

Pandas Advanced

8.5/10

Years Exp

ETL Advanced

8.0/10

Years Exp

Exploratory data analysis Advanced

8.0/10

Years Exp

Google Cloud Platform Advanced

8.0/10

Years Exp

Data Warehousing Advanced

8.0/10

Years Exp

Data Visualization Advanced

8.0/10

Years Exp

Data Integration Advanced

7.5/10

Years Exp

Docker Intermediate

7.5/10

Years Exp

scikit-learn Tableau NumPy Spreadsheets Microsoft Excel GGplot Seaborn Matplotlib Query Optimization Keras Statistical Analysis Hypothesis Testing Data Cleaning Data Wrangling Feature Engineering Predictive Modeling Business Analytics Window Functions CTEs JSON Bash DBT ELT Data Modeling Data Transformation Data Quality Batch Processing REST APIs SFTP CRM Integration Looker Studio BigQuery Cloud Storage Cloud Run AWS EC2 S3 Git GitLab CI LINUX Streamlit

Work Experience

Data Analyst

WebEngage

Aug 2022 - Present

Built an Adhoc Reporting Automation Platform using Python, SQL, Streamlit, and Google Cloud, automating nearly 70% of recurring reporting requests and reducing report turnaround time from 2–3 days to less than a day. Developed production-grade DBT models in Google BigQuery to build analytical data marts powering Streamlit dashboards for AOV, RFM Segmentation, Customer Journey Analysis, Product Performance, and Event Analytics; deployed the solution using Docker and GitLab CI/CD. Designed an ETL pipeline for Product Usage Analytics using Python, SQL, BigQuery, and Google Cloud, transforming raw product events into business metrics and building Looker Studio dashboards consumed by Product, Engineering, Sales, and Customer Success teams. Performed root cause analysis on Push Notification Reachability, using advanced SQL analysis to identify reasons behind declining delivery rates. Developed a reusable analysis framework that reduced investigation time by 7 days for future client engagements. Built sentiment analysis pipelines by extracting conversations from Slack APIs, processing text using Python, and generating actionable insights that enabled Customer Success and Product teams to proactively address client concerns. Developed scalable ETL pipelines to ingest customer data from SFTP servers, CRM platforms, REST APIs, cloud storage, and client databases, performing validation, transformation, schema mapping, and loading the curated data into the WebEngage Customer Data Platform. Optimized large-scale SQL transformations in Google BigQuery by implementing incremental models, reusable DBT macros, and query optimizations, improving pipeline performance and reducing execution costs. Worked extensively across Google Cloud Platform (BigQuery, Cloud Storage, Cloud Scheduler, Cloud Run) and AWS (EC2, S3) to develop, deploy, schedule, and maintain production data pipelines and analytics applications. Built custom analytical reports using Python, SQL, Excel, and BigQuery to deliver insights into campaign performance, customer behavior, communication patterns, and user journeys for enterprise clients.

Application Support

NSEIT Ltd (CLSA)

May 2020 - Dec 2021

Supervised the operations of trading application OMNESYS. Programmed and edited shell scripts to automate processes and deploy application components on server. Built and provided SQL queries with relevant data to the stakeholders. Resolved production issues and made sure it does not turn into a showstopper.

Application Support

NSEIT Ltd (NSE)

Sep 2018 - Mar 2020

Handled the operations of trading application NOW2.0, also managed version control of application components. Collaborated with stakeholders and solved production issues according to severity with the defined SLA time. Oversaw and deployed application packages on production and UAT server. Created application health check reports and reported them to stakeholders. Monitored resource utilization of application services via monitoring tool - 'Zabbix'.