Ai Engineer Data Quality

Rutwik Patil

+1-252-***-**** **********@*****.*** www.linkedin.com/in/rutwikpatil14

(Open to Relocate)

SUMMARY

I’m a Data & AI Engineer with 5+ years of experience helping organizations turn complex data into practical, scalable solutions. My work spans building AI chatbots, RAG pipelines, and multi-agent systems, as well as automating data workflows with dbt, Snowflake, and cloud platforms like AWS and GCP. I focus on creating reliable, compliant, and business-ready systems that reduce manual effort, improve data quality, and drive real impact across healthcare, education, telecom, and manufacturing.

WORK EXPERIENCE

Pn Automation Maryland, US

Data & AI Engineer Jan 2025 - Sep 2025

Designed and deployed AI agents for healthcare clients that automated the work of 40 manual roles, reducing task completion time from 1600 work hours to just 8 hours a week.

● Fine-tuned GPT-4o and Llama-4 models to reach 95% precision in predicting user intent across 3 categories.

● Automated data wrangling and validation using AWS S3 and Lambda, cutting manual intervention by 80%.

● Built Docker images with pre-configured dependencies (Python) to containerize data cleaning, preparation, and transformation scripts.

● Automated data transformation and quality checks with dbt models in Snowflake, structured under a medallion architecture (bronze–silver–gold layers) to deliver clean, reliable, and AI-ready datasets.

● Ensured HIPAA compliance by encrypting PHI in transit and at rest (AWS S3 with access controls).

● Developed a multi-agent AI PoC for Sales, with one agent on structured data (Redshift) and another on unstructured data (S3 + OpenSearch).

● Implemented retrieval-augmented generation (RAG) by connecting Langchain with Snowflake Cortex Search/Document AI and embedding pipelines, enabling contextual data retrieval across structured and unstructured data.

University of Maryland Maryland, US

AI Engineer Dec 2023 - May 2025

Project 1: Department of Decision Operations & Information Technologies Drove AI adoption by developing practical AI solutions, guiding teams on data governance, and establishing the groundwork for future AI integration across the department.

Built an AI-powered chatbot using Google PaLM LLM, and python scripts, enabling natural language queries to be converted into optimized SQL/MySQL retrieval pipelines for small businesses.

Built an AI-powered chatbot leveraging Langchain, Snowflake Cortex, and OpenAI APIs, enabling natural language queries on student data and delivering context-aware insights for management and academic users.

Championed data governance for AI projects, establishing data quality checks, metadata standards, and lineage tracking to align with AI model lifecycle management best practices.

Integrated VectorDB (Pinecone) for optimized chunking, retrieval, and RAG-based context management across unstructured healthcare and sales datasets.

Project 2: Education Abroad Office

Addressed delays and lack of visibility in the university’s manual course approval process, which relied on Google Drive and multiple advisor signoffs. Automated the workflow using Salesforce, integrated internal databases, and implemented real-time tracking via a custom dashboard, reducing approval time from over a day to under an hour.

● Led end-to-end business analysis for automating the course approval process, reducing approval time from over a day to under an hour by designing Salesforce workflows and integrating internal databases.

● Conducted stakeholder interviews and workshops to gather functional and non-functional requirements; documented findings through detailed BRDs, mockups, and process flows using Lucidchart.

● Collaborated with university IT and legal teams to align the automated approval process with FERPA data handling guidelines, especially regarding third-party integrations and data storage. Hughes Network Systems Remote, US

Data Engineer May 2024 - Aug 2024

Manual order placement and status tracking with vendors like AT&T and Comcast caused delays, frequent errors, and operational inefficiencies due to reliance on emails and Excel files. Developed a robust backend system using vendor APIs and engineered scalable data pipelines on Google Cloud Platform, automating the entire order lifecycle.

● Engineered scalable data pipelines on Google Cloud Platform using Dataflow/Spark, BigQuery, Cloud functions, and AlloyDB, reducing order processing times by 35%.

● Collaborated with stakeholders to establish data ownership and stewardship roles, promoting accountability for critical order lifecycle data and enabling effective issue resolution.

● Implemented data lineage tracking using GCP’s native tools and metadata tagging to provide full transparency of data flow across ingestion, transformation, and storage layers.

● Collaborated with business stakeholders and the DevOps team, gathering requirements, and creating Source-to- Target Mapping (STTM) documents to define ETL processes and ensure accurate data ingestion and transformation.

Lechler Mumbai, India

Data Analyst Sep 2021 - Jun 2023

Fragmented data sources, manual reporting workflows, and limited visibility into quality and equipment metrics hindered root-cause analysis and proactive maintenance at Lechler. Built automated data pipelines and predictive analytics solutions to enhance data quality, accelerate reporting, and support operational decision-making.

● Created a comprehensive KPI catalog tool mapping reported metrics to their respective dashboards, streamlining performance tracking, and improving stakeholder accessibility.

● Built an automated data cleansing pipeline using Python (Libraries- pandas, numpy, plotly) to detect and rectify errors (missing values, type mismatches, duplicates), reducing data prep time by 30%.

● Developed advanced Power BI dashboards to monitor production anomalies and quality deviations, resulting in a 40% increase in the detection of manufacturing inefficiencies. Mosdorfer Mumbai, India

Data Analyst May 2020 - Feb 2021

Siloed department-level data, inconsistent reporting formats, and outdated visualization methods at Mosdorfer led to inefficiencies in data consolidation and decision-making. Streamlined data operations by integrating performance data across departments and developing interactive dashboards to enable visibility into key operational metrics.

● Designed and implemented an ETL pipeline to seamlessly process data from multiple branch locations and miscellaneous formats. Standardized data integration processes, reducing processing time by 20%.

● Developed a regression model in python to accurately forecast resource utilization, reducing prediction errors by 20% and improving schedule tracking efficiency by 23%.

● Led the establishment of comprehensive data governance frameworks and defined clear program goals, roles, and responsibilities. Instituted rigorous data standards, policies, and processes to enhance data accuracy across the team.

● Led a cross-functional initiative to address rising labor costs by developing a dashboard to analyze contractor and vendor spending. Implemented strategic metrics that improved resource allocation, achieving a 9% reduction in labor expenses.

SKILLS

● Databases: Microsoft SQL Server, MySQL, MongoDB

● Programming Languages: Python (NumPy, Pandas, Matplotlib, Scikit-learn, PyTorch, NLTK, Plotly), R (Shiny, dplyr, ggplot2)

● GenAI/LLMs: GPT-4o, Llama, Langchain, Snowflake Cortex, OpenAI APIs, RAG, multi-agent AI, VectorDB (FAISS, Pinecone, Weaviate), Langchain loaders, leaderboard evaluation.

● Data Visualization: PowerBI, Tableau, Looker, QuickSight

● Big Data Tools: Snowflake, Alteryx, AWS Redshift, Google BigQuery, PySpark, Hadoop

● Machine Learning: Supervised ML (Linear and Logistic Regression, Decision Trees, RF, XGBoost), Unsupervised ML (K-means), NLP, Classification techniques (binary classification, multi-class classification), A/B testing, ROC- AUC Curve Analysis, Confusion Matrix

EDUCATION

● University of Maryland College Park, US

MS in Information Systems (GPA: 3.7/4) Aug 2023 - Dec 2024

● Narsee Monjee Institute of Management Studies Mumbai, India BE in Electronics and Telecommunications (GPA: 3.11/4) Aug 2016 - Dec 2020

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