Experienced Data Analytics Engineer with over 8+ years in Ed-Tech & Healthcare industry. Excellent reputation for resolving problems and improving customer satisfaction. Offers flexible schedule to deliver on team goals.
Overview
10
10
years of professional experience
1
1
year of post-secondary education
1
1
Certification
Work history
Data Analytics Engineer
Houghton Mifflin Harcourt
Pune
11.2024 - 03.2025
Company Overview: Ed-Tech company
Led projects on data migration using DBT and Snowflake to transition data from data lake to data warehouse
Handled designing data models and performing transformations, including parsing JSON files, flattening nested structures, and ingesting raw layer data into staging layer within data warehouse
Ensured local checks are run before code migration and adhered to DBT best practices to maintain code quality and optimise Snowflake migration process
Developed Tableau reports hosted on Tableau Server, ensuring seamless integration with newly established Snowflake database credentials within organization
Developed and implemented data models by utilising DBT to design and implement robust data models, including star and snowflake schemas, ensuring efficient data organization and retrieval
Integrated data from various sources using DBT, streamlining data pipelines and improving data accessibility by using complex SQL queries to perform data transformations, enhancing data quality and usability
Implemented tests and documented data models within DBT to maintain high data quality and ensure comprehensive data understanding
Ensured accurate data lineage and traceability by managing metadata effectively within DBT.
Formulated comprehensive DBT Quality tests, to verify product functionality and adherence to specifications; improved product release quality by 60%.
Worked closely with cross-functional teams, including data engineers and stakeholders, to deliver data-driven insights
Developed and maintained visualisations in Tableau, providing insightful and actionable data reports for e-learning platform along with performing data integration in tableau
Collaborated closely with data engineers and stakeholders to deliver actionable insights and support data-driven decision-making and implemented best practices for data management and governance to maintain data integrity and accuracy
Additionally worked as Scrum Master in team facilitating Agile process and fostering team self-organization to deliver valuable outcomes efficiently
Object Detection and Annotations among Males and Females - Goal of project included deep learning model to detect hair loss grades in males and females
Developed work on data gathering, cleaning, integration, dataset creation, model training, image processing, and image annotations using Label-Me
AI in Healthcare - Built process to create multi-class classification model on hair loss data which included Data Journalism, Data Collection, Data Preprocessing which includes data cleaning, designing and training models transformation in Python, Deriving and Interpreting data
Working on visualisation techniques and tools (Power-BI and Tableau) for story telling to solve business challenges, derive, analyse, and effectively present results of data analysis
Part of 3 member team, responsible for procuring new AI platform for Hair-Transplant.Ai
Evaluation, Testing, and implementation of platform along with data engineers
Led five-member software QA testing and data team in developing and implementing quality-assurance and data modelling methodologies to ensure compliance with QA standards, regulations and customer specifications for Healthcare insurance project in agile methodology
Implemented analytics tools for data-driven decision-making, conducted research on business and system requirements, market trends, and data management standards, assessing impact of requirement changes on project testing activities
Identified large and complex data sets and integrating it, data cleaning and pre-processing, exhibited test scenarios, estimated test effort and created test plans and improving data quality checks for each project
Created key metrics and supporting audit processes to ensure established goals were met
Ensured that delivered products and services meet all applicable internal and external standards, as well as client expectations and any applicable legal requirements
Took ownership, identified, assessed, monitoring, documentation, and communicating potential quality issues in way data is collected, stored, processed and used and analyzing test results to create test reports subsequently communicating reports to business partners and stakeholder management
Technology Stack - Power-BI, Tableau, Python, Microsoft Excel, Selenium, Manual Testing, JIRA, Confluence, SQL, Power-BI, JIRA, HP ALM, Agile, IBM RTC and RQM, Manual Testing