Harshal Shah
Data Wizard Extraordinaire
Email: harshalshah71@gmail.com
Phone: +61466341104
Web: www.shahharshal.com
Introduction
Welcome to my versatile profile, where I bridge the realms of data engineering, data science, software craftsmanship, and AI innovation. I am a data enthusiast with a penchant for transforming raw data into actionable insights, uncovering patterns and trends, crafting efficient software applications, and exploring the frontiers of artificial intelligence.
With a leadership mindset, I foster innovation, problem-solving, and continuous learning across these dynamic domains. My work exemplifies the synergy between technology and leadership, driving progress and efficiency. This website offers a glimpse into my multifaceted world, where I blend technical expertise with a vision for the future. Join me on this exciting journey of shaping the digital landscape, whether you’re interested in data, software, or cutting-edge AI technologies. Together, we can leverage the power of data and technology to transform industries and society.
Professional Profile
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Recent Work
Recent Jobs
Jan 2021 – now
Zetaris Pty Ltd, Melbourne, Australia
Full-time
Data Engineer
AI-Powered Data Empowerment: I developed a cutting-edge tool that harnesses the power of Generative AI (LLMs) and Zetaris to empower users, enabling effortless data interaction, data dictionary generation, data lineage tracing, and one-click task execution for structured, unstructured and semi-structured data.
Cloud Expertise: I deployed and configured Zetaris on AWS EC2 instances, Azure VMs, and Docker containers, aligning solutions with client requirements and infrastructure specifications.
Innovative Data Solutions: I created innovative solutions for change data capture, delta load, and schema change notifications using SQL, Python, Bash, and real-time data pipelines on the Zetaris platform.
Automation Mastery: Leveraging AWS Lambda, CloudFormation, and Event Trigger services, I automated Zetaris API calls, scheduled data processing, and ensured Infrastructure as Code (IaC), all while setting up robust monitoring with Amazon CloudWatch.
Data Modeling Expert: Proficient in Data Vault dimension modeling, I ensured efficient data management and analysis using Zetaris Platform, SQL, Python, and Apache Airflow.
Workflow Optimisation: I scheduled and orchestrated workflows within the Zetaris platform and externally using Apache Airflow to optimise data processing and automate task execution.
Kubernetes Deployment: I deployed Helm charts in an on-premises environment, harnessing Kubernetes as the primary orchestration tool for containerised applications.
Data Modeling and Analytics: I designed and maintained Snowflake data models and schemas, optimising data organisation, storage, and query performance for advanced analytics.
Insightful Dashboards: I developed impactful, customised dashboards using Microsoft PowerBI and Zetaris via ODBC connections, enabling data-driven decision-making.
Data Warehousing Excellence: I created a scalable data warehousing solution using AWS Redshift, connected to Zetaris Virtual Data Marts, enabling real-time analytics for business stakeholders.
Database Migration Leadership: I led the migration of on-premises databases to Amazon RDS, significantly improving database performance and availability.
ETL and Data Accuracy: I designed robust data pipelines using Azure Data Factory, ensuring accurate and timely ETL for large data volumes from various sources, enhancing downstream analytics and reporting processes.
Thorough Documentation: I crafted comprehensive documentation, including Solution Designs, Technical Designs, and deployment strategies, facilitating seamless deployment and maintenance of data solutions.
Robust Testing: I designed and implemented automated test cases for Zetaris software using Selenium, ensuring the reliability and robustness of data engineering infrastructure.
Jun 2020 – Dec 2020
Data Disca, Melbourne, Australia
Part-time
Trainee Data Scientist
Problem-Solving Proficiency: I adeptly identified business challenges, ranging from NLP text classification to creating tailor-made visualisations that precisely met the unique needs of each project.
Holistic Data Science Solutions: I applied a traditional data science approach, leveraging Python, R, Tableau, and relevant libraries to tackle diverse problems, including classification, regression, and time series analysis, ensuring well-rounded solutions.
Feb 2020 – Oct 2020
The University of Melbourne, Melbourne, Australia
Part-time
Data Science Intern
Enhancing Student Success: I utilised Python and a range of machine learning algorithms from the Scikit Learn library to predict and improve student success.
Achieving High Accuracy: Through meticulous hyperparameter tuning, I achieved an impressive 87% accuracy for the Random Forest (RF) model in our prediction system.
Proactive Student Support: I integrated a scenario modeling system into our prediction system to proactively identify students at risk of failure, providing valuable support to help them succeed.
Dec 2019 – Jan 2020
The University of Melbourne, Melbourne, Australia
Full-time
Data Science Intern
Optimising University Infrastructure: I assessed the efficiency and sustainability of The University of Melbourne’s buildings, ensuring their functionality and environmental impact aligned with strategic goals.
Space Utilisation Insights: By analysing space and occupancy data in libraries, I identified areas experiencing overcrowding and developed strategies to improve user experiences.
High-Accuracy Predictive Models: I achieved approximately 90% accuracy with a variety of machine learning models, such as Support Vector Machines (SVM) and Random Forest (RF), making them ready for practical deployment to enhance decision-making and resource allocation.
Jun 2019 – Nov 2019
RMIT University, Melbourne, Australia
Part-time
Data Science Research Intern
Deidentification for Cortana Project: Successfully executed a deidentification task as part of Microsoft’s Cortana Project, ensuring data privacy and security.
Predictive Sequences with RNNs: Leveraged Recurrent Neural Networks (RNNs) to predict future activities using sequential data, contributing to advanced forecasting capabilities.
Jun 2018 – Jan 2019
Reliance Jio Infocomm Ltd, Mumbai, India
Full-time
Data Analyst
Data Expertise: Proficient in schema creation, data cleaning, and analysis tasks, with a strong command of Excel Macros and SQL for streamlined data handling.
Quality Assurance Specialist: Conducted meticulous manual testing of applications, ensuring their readiness for the Indian market, and upholding quality standards.
Effective Communication: Took the lead in team-level documentation and served as the team’s direct liaison with the Manager, facilitating seamless communication and reporting on project progress.
Skills
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Education
2019 – 2020
The University of Melbourne, Australia
Masters of Data Science
2014 – 2018
KJSCE, University of Mumbai, India
Bachelors of Technology in Computer Engineering