Hemanya Arora

About Me

Results-driven Data Engineer with experience designing and deploying scalable data solutions for high-impact analytics. Adept at end-to-end ETL, data modelling, and DevOps best practices, leveraging Python, SQL, and cloud-native technologies (Azure, Databricks). Possesses strong collaboration skills, working cross-functionally to deliver actionable insights that drive efficiency, cost savings, and data-driven innovation.

Github: https://github.com/hemanyaarora
City: Toronto, ON

Email: hemanya56@gmail.com
Freelance: Available

Open for collaboration on any interesting projects.

Volunteering Experience

Code Club Canada

Moderating and Co-facilitating regular sessions of coding clubs for students aged 8-12 and teaching them basics of programming languages like Python & Scratch with the virtue of Raspberry Pi projects.

References: Madelyn Cugno (Email: maddie@kidscodejeunesse.org)

Skills

Python

SQL

T‑SQL

SSIS, SSMS

Data Modeling

ETL

Databricks

Apache Spark

Azure Data Factory

dbt

Data Lakehouse Platform

Azure DevOps

Achievement

Databricks Data Engineer Associate

Resume

Work Experience

Data Engineer: Cineplex Entertainment

April 2024 – Present

Production-Grade Pipelines: Designed and optimized large-scale ingestion pipelines (Azure, Databricks, ADF, dbt) to deliver reliable data for analytics and ML workflows.
Legacy Cube Modernization: Migrated SSIS-based cubes into Databricks’ medallion architecture, implementing new fact/dimension tables to power critical revenue (Moneyball) reports.
Strategic Cost-Optimization: Led the discovery of a partner-provided data service, mitigating an estimated $150K in licensing expenses while maintaining data coverage.
DevOps & Automation: Established CI/CD pipelines, service principal authentication, and robust monitoring/alerting to minimize ingestion failures and ensure data security.
API Refactoring: Transitioned data pipelines (e.g., YouTube, Wikipedia) from web scraping to official APIs, boosting reliability, security, and maintainability.
ML Pipeline Collaboration: Partnered with Data Science teams to refine data workflows, enhance performance, and ensure high data quality for advanced analytics use cases.

Data Science Intern: Kinaxis

September 2022 – December 2023

Data Modeling & ETL: Prototyped data-driven models and optimized feature engineering processes, improving AI frameworks for supply chain forecasting.
ML Workflow Optimization: Analyzed feature importance and implemented automation algorithms to streamline data segmentation, yielding more accurate forecasting outcomes.
Large-Scale Data Handling: Conducted data transformations and exploratory data analysis using Python and PySpark, with a strong focus on data security, compliance, and performance.
Agile Collaboration: Engaged in daily scrums with cross-functional teams, ensuring alignment of project deliverables with business goals.

Business Intelligence Analyst (Co-op): Co-operators

August 2021 – October 2021

Developed BI solutions (MicroStrategy, IBM Netezza) to improve reporting and analytics.
Optimized and validated SQL-based data extractions, ensuring accuracy and consistency.
Analyzed relational and non-relational data structures to contribute to more efficient data pipelines.

Programming Instructor: Code Club Canada

September 2020 – September 2022

Educated students aged 8–12 in programming basics and Raspberry Pi projects, fostering an early interest in technology.

Certifications & Technical Skills

Certified Databricks Data Engineer Associate: Passed on March 9, 2025 (Highlight)
Machine Learning – Coursera (Offered by Stanford University), Issued September 2022

Technical Skills

Programming: Python, SQL, T‑SQL
Big Data & Cloud: Databricks, Azure Data Factory, dbt, Apache Spark, Hadoop (HDFS), Azure DevOps
Data Engineering: ETL, data modeling, CI/CD, data orchestration
Visualization: Power BI, Tableau, Plotly
Workflow/Collaboration: Jira, Confluence, Git (GitHub), Agile/Scrum