Wavicle Data Solutions

Lead Data Engineer

LinkedIn

LinkedIn Learning Instructor

Globant

Senior Data Engineer

CRISIL Limited

Senior Analyst - Data Engineer

Quantiphi

Data Engineer

Tata Consultancy Services

System Engineer

Assistant System Engineer

Assistant System Engineer - Trainee

InsideSherpa

KPMG Data Analytics Consulting Virtual Internship

Monisha Enterprises

•	Data mining and Extraction Transformation Loading using R programming.
•	Data cleaning and processing for Data analysis done using Python using NumPy, pandas, SciPy, Scikit. Data modelling and prediction was done using algorithms – Logistic Regression, Time Series Forecasting, Clustering and Classification.
•	Data Visualization done using Tableau for generating reports to enhance the productivity of the products.
•	Built a Data Warehouse on MSSQL Server for ERP System of the enterprise to organize the data for future processing.

Data Analyst Intern

Open to Collaborate | Storyteller | Lead Data Engineer@Wavicle| Linkedin Top Voice 2024 | Globant | Linkedin Learning Instructor | 2xGCP & AWS Certified | LICAP'2022

Data Engineer with 7+ years of experience working on data engineering, analysis, and modelling projects for various domains, such as banking, healthcare, sales, and e-commerce. I leverage my strong statistical and analytical ability to explore business ideas and provide innovative solutions. 

Skilled with technologies and strong intellect with enthusiasm as an avid learner with challenging opportunities. I’m working as a LinkedIn Learning Instructor to bring change as a data evangelist.

Post Graduated in Master of Technology in Data Science and Engineering from Birla Institute of Technology and Science, Pilani in 2023, where I learned advanced concepts and techniques in data science and engineering, machine learning, cloud computing, and visualization. 

I hold multiple certifications in GCP, AWS, and Azure, and I enjoy working with cloud technologies and big data platforms.

I am passionate about data science and women empowerment, and I have been recognized as the 
- Linkedin Top Voice 2024 
- Data Science and Women Empowerment Thought Leader by Global AI Hub. 

I am also a proud participant of the LinkedIn Creator Accelerator Program 2022, where I share my insights and experiences with the data science community. 

I am open to collaborate and share ideas, or explore various opportunities in the data field.

Pooja Jain

73% of data pipeline failures happen because of dependency issues, not bad code.
Cron jobs don't care if yesterday's data never arrived. They'll happily run on empty tables and produce garbage.

Airflow? It checks, retries, alerts, and refuses to cascade your failure downstream.

→ Beyond scheduling Airflow gives an important feature of 𝗗𝗔𝗚𝘀(𝗗𝗶𝗿𝗲𝗰𝘁 𝗔𝗰𝘆𝗰𝗹𝗶𝗰 𝗚𝗿𝗮𝗽𝗵𝘀), that helps to monitor, retry and gives flexibility to organize pipelines with minimum/less code.

🤔 Data Engineers often misinterpret Airflow just as an orchestration tool.

Apache Airflow is an open-source platform designed to programmatically author, schedule, retry and monitor workflows. 

🎼Think of it as the "conductor of an orchestra", where each musician (your data tasks, like data extraction, transformation, loading, or model training) knows when to play, what to play, and what happens if they make a mistake.

Most data engineers automate the wrong things at the wrong time.

Here's the framework I use after 8 years of building production systems:
✅ AUTOMATE WHEN: 
→ Task runs daily/weekly 
→ Human errors cause outages 
→ Work blocks other priorities
→ Team growth = more manual work
Examples: Reports, schema checks, alerts

❌ DON'T AUTOMATE WHEN: 
→ Task happens quarterly 
→ Requirements change weekly 
→ Process isn't understood yet 
→ Manual steps reveal insights

My rule: If it’s done 3+ times, script it; 10+ times, automate it; fails 5+ times, redesign it.
Automate what matters, when it matters—not everything!

Airflow isn’t just about running tasks.

🕑 It’s about building trustworthy, scalable, and observable pipelines that run reliably at 2am — even when you’re not watching.

Airflow gives structure to your chaos.
DAGs give clarity to your pipelines. 
That’s why DEs love them ❤️

Real Example: 
Instead of: 
❌ Cron jobs that fail silently 
❌ Manual dependency management
❌ No visibility into failures
You get: 
✅ Visual workflow monitoring 
✅ Automatic failure notifications
✅ Smart task scheduling 
✅ Easy debugging & restarting

Here's an amazing Airflow cheatsheet with some fundamentals concepts and interview questions to prepare for data engineers. 👇

Carousel Credits -  Futurense.com

Willing to learn more, here's the link to Astronomer free learning path - https://lnkd.in/g8-EWBda

Also, level up with Marc Lamberti's Udemy course on Airflow 3 - https://lnkd.in/gwArwaME

Airflow

Medium

✍ Author of Articles on the Trending Topics of Generative AI, Data Science, Artificial Intelligence, Data Analytics, Machine Learning, Python, Deep Learning, Computer Vision, Natural Language Processing (NLP), MLOps, LLMOps, New Emerging technologies, Technical Data Science blogs, Career Guidance and Learning Tips.

Technical Writer

RyDOT Infotech Pvt Ltd

• Research & Development of Generative AI Use cases using Open Source LLM Models & Frameworks.
• Deliver NLP and machine learning-based solutions to address diverse real-world challenges effectively.
• Proficient in gathering requirements from the Business Team, ensuring alignment with organizational objectives and needs.
• Employ Deep learning, NLP and machine-learning methodologies to tackle real-world challenges, selecting and implementing solutions tailored to specific business requirements. Analyze data for emerging trends and patterns, interpreting findings with a clear strategic objective in mind.
• Leveraged state-of-the-art language model architectures such as GPT and BERT for natural language understanding tasks and applied transfer learning techniques for fine-tuning pre-trained language models for specific downstream tasks, while ensuring seamless integration into LLMOps pipelines for efficient deployment and monitoring.
• Projects: Generative AI Usecases, RAG Chatbot, Speech Prosody Recommendation App, AI Lipsing Sync App with Custom Voices, Predictive Modelling, AI Music Generation, RAG Evaluator, AI Agents.

Data Scientist

PUBLIC WORKS DEPARTMENT 

•	Data Analysis: Formulation & Analysis of Detailed Estimates & Rates
•	Financial Analysis: Estimation & Valuation of Building Reports
•	Preparation of NIT's (Notice Inviting Tenders Documents)
•	Composing Deviation Statement’s 
•	Software Maintenance & Quality Assurance
•	Develop and Implement strategies to achieve organizational goals
•	Evaluating and formulating enhancement strategies to boost KPIs, etc.
•	Decision-Making And Planning with Formulation & Analysis of Monthly Report Generation of Works
• It was Freelance work as Data Analyst Trainee to support projects & gain handson experience whenever work was allocated by Central Government Officer. 
• It honed my problem-solving and analytical abilities, enabling me to approach complex data science challenges with a strategic mindset, evidence-based decision-making in real-world scenarios and optimizing processes.

Data Analyst

Income Tax India Official

Central Public Works Department, Govt. of India

Indian Institute of Management Ahmedabad

•	Assisting Faculty members with Academics and Research with Case Writing, Teaching Note/Exercise Development And Paper Writing With Updating Of All Tools, Techniques And Software Applications For Conducting High Quality Research. 
•	Grading, Invigilation, tracking progress for all the courses (projects, quizzes, assignments, sheets, etc.). 
•	Providing Teaching aid to the students.
•	Coordinating with all Academic offices (PGP, PGP-ABM, PGPX, FPM, FDP, MDP & other support offices). 
•	Participation in all Briefings, Discussions And Trainings at all levels.

Academic Associate

Nirma University, Ahmedabad, Gujarat, India

Pursued M.Tech in Computer Science & Engineering with Specialization in Information And Network Security.

Professional

Government Polytechnic College

Mentor in Computer Science Branch, Skills Enhancement Of Students.

Lecturer

Microsoft Azure Cert. Data Scientist👩🏻‍🎓| IIIT-B | Former AA: IIM-A | Former Analyst: Central Govt. Of India | AI Researcher| MLOps| Computer Vision| Data Science| ML | NLP | Deep Learning | LLMs| LLMOps| AWS🏆

👩🏻‍🎓 Data Scientist || Generative AI Researcher || MLOps || LLMOps||  Data Science || Machine Learning|| NLP || LLMs || DL || CV || Python || SQL || Azure || AWS || Scholar || Hackathon Winner|| Open Source Contributor || Technical Content Writer || Thought Leader 

🎯 In my 2+ Overall Diverse Professional Experience in different roles, I've dealt with Data Analytics, Financial Analytics, Security Analytics, Statistical Analysis, Data Visualization, Data Mining, Problem Solving, Decision-Making & Planning, Software Quality Assurance, Information Technology, Information Security, Data Security, Research & Development (R&D).

🎯Adept at Performing Deep dive to Gain Actionable Insights with Excellent Data Analytical Skills, proficient Decision-making capabilities & Problem-solving skills 

★ 𝐂𝐨𝐦𝐩𝐞𝐭𝐞𝐧𝐜𝐢𝐞𝐬: Artificial Intelligence| Data Science| Machine Learning| Data Analysis| Deep Learning| Natural Language Processing| Computer Vision| Data Mining| Data Processing|  Data Visualization| Data Modeling| Predictive Modelling| Statistics| Text Analytics| Prompt Engineering| Optimization| Hypothesis Testing| Python| Azure| AWS| LLM| MLOps| LLMOps| Explainable AI| Generative AI| Debugging| Deployment

★ 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: Python, R, Data Mining, Data Processing, Modeling, Data Visualization:Tableau

★ 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚 𝐓𝐨𝐨𝐥𝐬: Microsoft Azure Certified, AWS

★ 𝐌𝐋: Supervised- Unsupervised Learning, Linear - Logistic Regression, Random Forest, Clustering, Feature Engineering, PCA, Bagging, Boosting , Model Selection, Time Series Forecasting

★ 𝐃𝐋:
Neural Networks, RNN, LSTM, GRU, CNN, Back Propagation, Transfer Learning, Optimization of Algorithm, Regularization, Hyperparameter Tuning, Batch Normalization
✓ Object Detection Algorithm : YOLOv5, SSD, RetinaNet, R-CNN, Faster RCNN, Efficient Det
✓ Semantic Segmentation Algorithms: Unet, FCN, SegNet, DeepLab, DeepLabv3 , Unet++
✓ Generative Adversial Networks
✓ Instance Segmentation, Vision Transformer, Autoencoder, Capsule Net, RBF, Deep Belief Network, Variance Auto Encoder, Wavelet CNN, etc

★ 𝐍𝐋𝐏 
Tokenization, Stemming and Lemmatization, POS Tagging, NER,, Sentiment Analysis, Topic Modeling, Text Classification, Word Embeddings, Seq2Seq Models, Attention Mechanisms and Transformers, Language Modeling.
• Frameworks: NLTK, Spacy, Gensim, Hugging Face's Transformers, torchtext, Stanford CoreNLP, Langchain
• Prompt Engineering, LLM’s, LLMOps with MLflow

★ 𝐒𝐨𝐟𝐭 𝐒𝐤𝐢𝐥𝐥𝐬: Mentorship, Leadership Development, Team Player, Communication Skills, Storytelling, Critical Thinking.

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The Battle

Pooja Jain

GURPREET KAUR JETHRA

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The Battle

Pooja Jain

GURPREET KAUR JETHRA

Followers

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Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Pooja Jain's LinkedIn Performance

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