Atin Maiti

Data Engineer, Senior Solution Specialist @ Deloitte

About

As a passionate Data Engineer with 8+ years of experience spanning data engineering and data science, I thrive at the intersection of innovation, scalability, and impact. I’ve had the privilege of designing and developing robust data architectures and systems that not only support business goals but help drive them forward. From building end-to-end pipelines to optimizing data flow and infrastructure, I approach every challenge with a big-picture mindset—always looking for ways to save time, boost profitability, and elevate user and stakeholder experiences. Learning is a lifelong journey, and I’m just getting started. I’m constantly exploring new technologies, frameworks, and approaches to stay ahead of the curve and ensure that the solutions I build are efficient, scalable, and forward-thinking.

Country

United States

City

Winter Park

Industry

Management Consulting

Skill

Apache Flink, Redis, Gateway, Grafana, Data Lakes, MongoDB, Apache Kafka, Kubernetes, Prometheus.io, Docker, Snowflake, Azure Databricks, Python, Tableau, Machine Learning, Data Analysis, Statistical Data Analysis, Business Analysis, Data Mining, Data Visualization

Experience

Data Engineer, Senior Solution Specialist

Deloitte

2025-5 - Present · 1 yr 5 mos

Orlando, Florida, United States

* Lead and Guide team to develop robust streaming and batch data pipelines. * Big Data workflow optimization * Prompt Engineering, LLM, GenAI * Data pipeline disaster recovery

Data Engineer, Solution Specialist

Deloitte

2022-5 - 2025-5 · 3 yrs 1 mo

Orlando, Florida, United States

* Design and Architect end to end streaming and batch pipeline. * Data modeling for structured and unstructured data. * Working with various aspect of ETL / ELT systems.

Data Engineer, Analyst

Deloitte

2021-5 - 2022-5 · 1 yr 1 mo

Tampa, Florida, United States

Strategy and Analytics, Applied AI and Data

Data Scientist (Full-Stack)

Energy4Life

2019-7 - 2021-4 · 1 yr 10 mos

Tampa/St. Petersburg, Florida Area

• Marketing Data Analytics: CLTV, Customer Lifetime Journey, and BI reporting • Working with unstructured data to provide meaningful insights on lifestyle and nutrition. • Understanding the problem, preparing data, data modeling/data analysis, visualize the data, present results, data modeling, production deployment. • Tools and Technologies: MS SQL Server, Python, Azure, JIRA, OpenCV, Docker

Intern - Data Science & Analytics

Nextech Systems

2018-8 - 2019-4 · 9 mos

Tampa/St. Petersburg, Florida Area

• Devised a solution by applying predictive modeling on patient appointment data to predict no-shows using statistical methods and ML models. The project involved data gathering and creating data pipelines using SQL and Python (Sklearn, Matplotlib, Imblearn, Pandas). Incorporated models like Decision Tree, Naïve Bayes, Logistic Regression, Random Forest with AUC and ROC as my performance criteria. • Developed an interactive dashboard for tracking the activities of users in the community portal in salesforce using Power BI and Salesforce reports. Was able to identify and reduce the mean age of response. • Classifying Images from data repositories to help categorize different types of images and hence saving time and increasing efficiencies.

Market Research and Data Analyst, Summer Intern

Nextech Systems

2018-5 - 2018-8 · 4 mos

Tampa, Florida

• Assessing the market within a few specific physician specialties with the help of research and visualization to facilitate decision making. • Process improvisation in a workflow to promote the organization's best practices and create a platform for data analysis for the coming years.

Assistant System Engineer

Tata Consultancy Services

2015-8 - 2017-7 · 2 yrs

Thane

• Analyzed data inputs to spot common trends and underlying problems. • Reprocessed records from incident management system to build a KB and dashboards. • Created customized reports in Salesforce CRM, received appreciations from the client. • Promoted from area support to BRM support within the first month. Monitored quality of ticket resolution, achieved 100% SLA. • Prepared and presented business requirement documents for new enhancement requests. • Fixed bugs in the production environment, with the help of SQL queries.