Sai Praveen
About Sai Praveen
Sai Praveen is a highly motivated and results-driven Analytics Engineer with over 3 years of experience designing, building, and maintaining scalable data pipelines and ETL workflows. He brings extensive expertise in cloud platforms (GCP, AWS, Azure), big data frameworks like Spark, and programming languages including Python and SQL.
With a proven ability to collaborate with business stakeholders and data scientists, Sai excels at unlocking business requirements and driving data-driven decision-making. His experience spans revenue operations, product analytics, and customer segmentation, delivering actionable insights that support strategic business initiatives.
A Master of Engineering graduate from the University of Toronto with an emphasis in Data Science, Sai combines strong technical skills with business acumen to deliver solutions that create measurable impact across organizations.
Professional Experience
Analytics Engineer - Revenue Operations | Geotab (2024 - 2025)
Built insightful revenue dashboards and reports tracking MRR, revenue shrinkage, ARPU, and churn. Data modeled and maintained gold standard datasets and pipelines related to sales and revenue operations, leveraged across Geotab providing critical metrics across 65k+ customers and 5M+ devices.
- • Defined and automated quality standards for large-scale data workflows, implementing alerting for table owners to resolve anomalies proactively
- • Developed, owned, and maintained 5 critical datasets on product usage, enabling unified insights for 10+ stakeholders in the product team
- • Collaborated to build a customer segmentation model based on Geotab product usage, delivering actionable insights and identifying key patterns
- • Acted as a trusted advisor and strategic thought partner to Product & Sales teams
Technologies: Google BigQuery, Python, Airflow, Google Analytics, Superset
Data Analyst | Siemens Limited, India (2018 - 2021)
Streamlined revenue data reports using SQL and crafted data visualizations with Excel and Power BI, saving teams several hours in manual workload. Involved in ETL processes and database management, data cleaning, manipulating, and storing data in databases.
- • Collaborated with cross-functional teams to study energy consumption data of several clients to provide customer success stories and marketing metrics
- • Created and maintained datasets for product pricing which helped the sales team reduce RFP response time from several hours to few minutes
Technologies: SQL, SAP, PowerBI, Engineering Management
Key Projects
GPS Streaming Pipeline
Built a pipeline to ingest real-time GPS data into Apache Kafka and store raw data in .txt files on a daily basis. Leveraged Airflow to perform ETL on a daily basis and load to MySQL for querying.
Skills: Kafka, Airflow, Docker, MySQL, Flask, Python
Analysis of Generative AI (Co-op) | Deloitte
Demonstrated the capabilities of LLMs by using LangChain and HuggingFace to build a question-answering chatbot on Deloitte reports and knowledge repository.
Skills: LangChain, HuggingFace, PowerBI
Smart Gallery | University of Toronto
Developed a smart gallery app with image caching, user image classification, and semantic search using text and voice, all hosted in an EC2 instance.
Skills: AWS CloudWatch, EC2, DynamoDB, S3
Technical Expertise
Cloud Platforms
- • Google Cloud (BigQuery, Pub/Sub, GKE, GCS, Cloud Composer, Cloud Functions)
- • Azure (Databricks, Data Factory)
- • AWS (DynamoDB, Lambda, S3, CloudWatch, EC2, Redshift)
Languages & Tools
- • Python, SQL
- • Apache Airflow, DBT
- • PySpark
Data Visualization
- • Apache Superset
- • Power BI
- • Plotly, deck.gl
Education
University of Toronto
- • Master of Engineering with emphasis in Data Science
- • 2022 – 2024