Shiivong Birla
Data Engineer Machine Learning Engineer



Data Engineer - NTT Data Australia
Master of Data Science - Monash University


About Me

  • Name : Shiivong Birla
  • Date of Birth : 27 February 1995
  • Email : shiivongbirla27@gmail.com

I am a Data Engineer / Machine Learning Engineer by profession, with a Master’s degree in Data Science from Monash University.

My expertise includes working with large data sets to come up with analyses that are in line with the company’s goals. In my previous roles, I have been responsible for creating visualisations to communicate key business insights to shareholders from multiple different teams. I excel at coming up with technical data solutions to help solve real-world business issues while effectively communicating these analyses, predictions, and ideas with the team and various shareholders to quickly come up with scalable prototypes to get a clear measure of growth.

Garnering work experience from the corporate firms of all sizes, I’m a critical thinker driven by the fascination of technology with an urge to create positive impact on businesses. Some of the domains I've worked in are Energy & Gas, Healthcare, Financial Services and Insuarance.

When I'm not breaking my head on fixing bugs in my code, you could find me playing Bass Guitar, playing Football or keeping upto date on Geo-politics. I am also deeply curious about the financial world, and actively invest in the growing Indian market.

  • Data Engineering
  • Microsoft Azure
  • Google Cloud Platform
  • Data Science
  • Data Governance (Microsoft Purview)
  • Advanced Data Analysis
  • Time-Series Forecasting
  • Natural Language Processing
  • Machine Learning
  • Deep Learning

Education

  • Jul'18 - Jul'20

    Master of Data Science

    Monash University, Melbourne, Australia

    Major - Big Data

  • Jul'13 - Jul'17

    Bachelor of Technology in Computer Science

    Vellore Institute of Technology, Vellore, India

    Major - Data Science

Work Experience

  • Feb'23 – Present

    Senior Data Engineer

    NTT Data Australia, Melbourne

    • • Collaborated with diverse stakeholders within the Department of Health to comprehensively analyze data sources owned by various business entities. Applied this understanding to proficiently deploy and configure Microsoft Purview's Identity Access Management and Security protocols, ensuring stringent control over access to sensitive data exclusively for authorized personnel. Additionally, played a pivotal role in crafting a robust Data Governance plan in conjunction with the team, delineating the project's goals, objectives, and an implementation roadmap. This strategic plan, encompassing essential resource requirements, is poised to enhance the Department of Health's Data Security and Compliance capabilities significantly.

      • Spearheaded the execution of the SAMS2 Reporting project by meticulously grasping its requirements. Innovatively designed and implemented YAML pipelines on Azure DevOps to automate the Continuous Integration/Continuous Deployment (CI/CD) processes for SQL objects. Simultaneously, developed intricate SQL scripts for stored procedures, functions, and tables, demonstrating adeptness in translating project requirements into tangible solutions. Concluding with the seamless deployment of SQL scripts to the Azure SQL Database through the YAML pipelines, the endeavor showcased a commitment to efficiency and precision in project execution.

  • Jun’22 - Dec'22

    Senior Data Engineer

    Mott MacDonald Australia, Adelaide

    • • Played a pivotal role in the advancement of Moata, an in-house Advanced Analytics proprietary tool hosted on Azure, by contributing to its development. Orchestrated the integration of the platform with key technologies such as Python, GitHub Actions, Logic Apps, and Power BI Dashboards. This integration facilitated a sophisticated data-driven approach to address Geo-spatial Time-series business use cases, encompassing critical areas like Network Capacity and Workload, Electricity Demand and Consumption, and Predictive Maintenance. Notably, the tool proved instrumental in proactively identifying faults well before they could manifest.

      • Demonstrated proficiency in developing Geospatial solutions using Python on ArcGIS Pro, strategically leveraging Python toolboxes to seamlessly interact with Moata. This involvement encompassed essential functions such as uploading, downloading, and updating Geospatial assets. The application of Python in this context showcased a nuanced understanding of both Geospatial technology and data management within the Moata framework.

      • Facilitated effective communication and collaboration among diverse Engineering teams, including Electrical, Mechanical, Structural, and Design, to comprehend and compile Business Requirements for Data-Driven Solutions. Led the initiative to evaluate the feasibility of Business Cases, ensuring alignment with organizational objectives. This role required adept coordination to bridge technical and business perspectives, fostering the development of innovative solutions grounded in comprehensive business understanding.

  • Nov’21 – Apr'22

    Senior Data Engineer

    KPMG Australia, Adelaide

    • • Spearheaded the development of a Proof of Concept (POC) in Tableau with a focus on forecasting metrics such as Revenue and Sales for a prominent convenience store flagship. The objective was to systematically identify suburbs with the highest retail growth potential, utilizing factors such as Population growth, Income growth, and Footfall. This data-driven approach aimed to provide actionable insights for strategic decision-making in expanding retail operations.

      • Utilized Terraform to orchestrate the deployment of Infrastructure on Azure, demonstrating adeptness in ensuring a robust and scalable foundation. Pioneered the development of Data Pipelines using Azure Data Factory to streamline the integration of data from diverse sources. Employing an efficient data wrangling process, the curated data was seamlessly transferred to Azure SQL Data Warehouse for further processing. The comprehensive workflow incorporated Continuous Integration/Continuous Deployment (CI/CD) practices with Git integration, showcasing a commitment to operational excellence in an internal Proof of Concept for a prominent logistics company.

  • Nov’20 - Nov’21

    Data Engineer

    Enzen Australia, Adelaide

    • • Engineered comprehensive Data Pipelines to efficiently ingest, integrate, clean, and process data from multiple sources, managing the volume of gas faults in the expansive network of Australia's largest Gas Infrastructure Group (AGIG). Leveraging Dataproc and BigQuery on Google Cloud Platform, the implemented pipelines showcased a robust and scalable solution for managing complex datasets.

      • Innovatively designed and implemented an advanced Forecasting model on Google Cloud Platform using the PyTorch-based NeuralProphet library within Jupyter Notebooks. This initiative resulted in a noteworthy 32% reduction in field resource allocation costs. Subsequently, enhanced the model's efficacy by integrating it with an Autoregressive Neural Network, achieving an additional 17% reduction in field resource allocation costs.

      • Conducted thorough Data Analysis on gas faults data, integrating the outcomes of the aforementioned forecasting model into a comprehensive Google Data Studio report. This end-to-end Predictive Modelling solution provided stakeholders with actionable insights and a holistic view of the gas network's performance.

      • Operationalized the developed model on Google Cloud Platform using Docker containers and Crontab, establishing a fully automated Forecasting process. This implementation not only ensured the sustainability of the Predictive Modelling solution but also streamlined and optimized the forecasting workflow for ongoing operational efficiency.

  • Jan’20 – Feb’20

    Junior Data Scientist

    Deloitte Australia, Melbourne

    • • Spearheaded the development and optimization of sophisticated Deep Learning models on TensorFlow, specializing in Time-Series Forecasting, Image Classification, Object Detection, and Natural Language Processing. Leveraging Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs), these models were intricately crafted atop Apache Spark on Azure. The focus on diverse applications underscored a versatile skill set in harnessing cutting-edge technologies for varied data-driven tasks.

      • Played an integral role within the Data Modernization team, contributing to the development of SSIS Data Pipelines, SSAS Cubes, and Power BI Reports within the Azure Data Factory framework. This collaborative effort aimed at enhancing data integration, analysis, and visualization capabilities, showcasing a commitment to modernizing data processes and facilitating informed decision-making within the organization.

  • Jan’17 - Jul’18

    Data Analyst

    KPMG India, Bengaluru

    • • Orchestrated end-to-end development solutions to establish a comprehensive Enterprise-wide Business Intelligence mechanism for Reporting. Utilized tools such as SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), and Power BI to seamlessly integrate and visualize data. This initiative aimed to empower the organization with robust reporting capabilities, fostering informed decision-making across various business units.

      • Applied advanced Machine Learning Algorithms in R and Python to tackle intricate business challenges within the Predictive Analytics domain. The optimization of these algorithms demonstrated a commitment to leveraging data-driven insights for strategic decision-making, contributing to enhanced business outcomes.

      • Innovatively designed and implemented a fully functional Business Process Mining Shiny application, serving as an in-house tool. This bespoke application showcased a nuanced understanding of business processes and data visualization, providing stakeholders with a powerful tool for process analysis and optimization.

Projects

Skills

Microsoft Azure

90%

Google Cloud Platform

75%

Python

90%

SQL

80%

R

70%

Scala

20%

More skills

Power BI
Git
Tableau
Computer Vision
Time-series Forecasting
Natural Language Processing

Recommendations

  • Dec'21

    Alex Osti

    Technical Director, Mott MacDonald Australia

    Shiivong was a delight to manage. Always positive, hungry to learn and improve, his attitude was as good as one could hope for in a team member.

    During his time with Mott MacDonald, Shiivong made great strides in transitioning the application of his fundamental technical knowledge from single use cases to scalable production-ready code that underpinned cloud deployments and unlocked high value outcomes for our infrastructure sector clients.

    He made a significant and positive impact during his time at Mott MacDonald and will be missed.

  • Feb'20

    Beena Rao

    Senior Specialist Lead, Deloitte Australia

    Shiivong is an extremely proactive Data analyst with a good mix of technology and functional understanding. I was extremely impressed by his effort and productivity within the team while working with him. I wish Shiivong the best of luck with his future projects.

  • Nov'18

    Rakesh Paul

    Manager, KPMG India

    I rarely come across real talents who stand like Shiivong. I had the pleasure of working with Shivong for product development, collaborating on several aspects of different tools. His perseverance to handle such heavy lifting in earlier phases of his career made a huge impact on the faster solution development.

    Process Mining being a niche skill set, he was able to grasp the subject and played a pivotal role in bringing the tool at a significant mature stage. As a team member, Shiivong earns my highest recommendation, a stellar performer indeed.

  • Aug'18

    Nikita Purnaye

    Data & Analytics Manager, Unilever

    Top notch attitude, great problem solving skills, ability to grasp things at drop of a hat and a fun person to work with, Shiivong brings a lot of dynamism, creativity and dedication to the table.

    I worked with Shiivong for almost a year in very critical project of Healthcare services client for BI implementation. He learned SSIS, SSAS and Power BI in no time and started handling a critical module in project independently. He owned the module end- to- end, right from requirement gathering, logic/ source system understanding, implementing and designing dashboards. Shiivong received appreciation from all client senior/executive management for his amazing work for the executive dashboard.

    Shiivong went out of his way and leveraged his R and Shiny skills to help a new solution development in KPMG analytics practice while handling the strict deadlines at client project deliverable. His contribution during nascent stages of the solution, helped team a lot to develop it further. I wish Shiivong a very bright career and best wishes for his future endeavors.

  • Jul'18

    Megha Chandni

    Azure Data Engineer, Nokia

    Shiivong is a hardworking and professional person. He is a quick learner and has a right attitude towards learning. He joined as an intern in KPMG and continued as analyst. He independently completed 4 modules of a project with minimal issues. He picked up MSBI skill in very short time and has good knowledge in SQL as well.

    As a senior, I have reviewed his work and it was good to see that his work is praiseworthy. Besides MSBI, he worked on R analytics side by side for process mining. Overall he is a good person.

Publications and Certifications

  • 2022

    Lakehouse Fundamentals

    Databricks

    • The Databricks Accredited Lakehouse Platform Fundamentals accreditation exam will test your knowledge about fundamental concepts related to the Databricks Lakehouse Platform. Questions will assess how well you know about the platform in general, how familiar you are with the individual components of the platform, and your ability to describe how the platform helps organizations accomplish their data engineering, data science/machine learning, and business/SQL analytics use cases. Please note that this assessment will not test your ability to perform tasks using Databricks functionality. Instead, it will test how well you can explain components of the platform and how they fit together.

    See certification

  • 2022

    Azure Enterprise Data Analyst Associate

    DP-500

    • Help collect enterprise-level requirements for data analytics solutions that include Azure and Power BI.

    • Advise on data governance and configuration settings for Power BI administration.

    • Monitor data usage.

    • Optimize performance of the data analytics solutions.

    Verify via Credly

  • 2022

    Microsoft Azure Data Engineer Associate

    DP-203

    • Azure Data Engineer Associate certification validates the skills and expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions. Candidates have a solid knowledge of data processing languages, such as SQL, Python, or Scala, and they need to understand parallel processing and data architecture patterns.

    Verify via Credly

  • 2020

    Natural Language Processing Specialization

    DeepLearning.AI

    • Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies, translate words, and use locality-sensitive hashing to approximate nearest neighbors.

    • Use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in TensorFlow and Trax to perform advanced sentiment analysis, text generation, named entity recognition, and to identify duplicate questions.

    • Use dynamic programming, hidden Markov models, and word embeddings to autocorrect misspelled words, autocomplete partial sentences, and identify part-of-speech tags for words.

    • Use encoder-decoder, causal, and self-attention to perform advanced machine translation of complete sentences, text summarization, question-answering, and build chatbots. Models covered include T5, BERT, transformer, reformer, and more!

    See certification

  • 2020

    TensorFlow Developer

    DeepLearning.AI

    • Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for a computer vision applications.

    • Build natural language processing systems using TensorFlow.

    • Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.

    • Apply RNNs, GRUs, and LSTMs as you train them using text repositories.

    See certification

  • 2016

    Machine Learning on Imabalanced Data in Credit Risk

    IEEE Xplore

    • Co-authored a paper on Machine Learning on Imbalanced Data in Credit Risk, published in an IEEE paper publication to address the problem of privacy in Data Mining and to suggest a simple yet effective way to preserve the privacy by hiding the sensitive data before using Data Mining algorithms.

    To access the paper, See publication

  • 2015

    Data Mining on Student Database to Improve Future Performance

    International Journal of Computer Applications

    • Co-authored a paper on Data Mining on factors that affect a students' performance at school.

    To access the paper, See publication

Get in touch



Location Melbourne, Victoria, Australia 3000
E-mail shiivongbirla27@gmail.com