Data Pipelines · ML Systems · LLM Tooling
Sharad
Chandel.
Currently building data pipelines for marketing analytics.
I build scalable data pipelines and data-driven applications — around 7 years deep in pipelines, warehousing, and data modeling. Alongside that, I have shipped AI/ML projects spanning customer segmentation, recommendation systems, and LLM-powered tooling. Currently leading the data engineering team at DWAO, a leading martech company. I work day-to-day in Python, Golang, Node.js, SQL, and the major cloud platforms — AWS, GCP, and Azure.
- Data Pipelines
- ETL
- Streaming
- Warehousing
- Customer Segmentation
- Recommendation Systems
- LLM Tooling
- Feature Stores
- Model Deployment
- Real-time Analytics
- Python
- Go
- Node.js
- SQL
- AWS
- GCP
- PostgreSQL
- Snowflake
- Databricks
- scikit-learn
- PyTorch
- LangChain
- MLflow
Selected Work
Where I've been shipping data systems.
2021 - Present
Data Engineer
Digital Web Analytics and Optimization LLP
Leading the data engineering team in designing and maintaining robust data pipelines and systems using Python, SQL, Golang, NodeJs. Developed and implemented efficient ETL processes, integrating data from various sources such as Google Analytics 4, Mixpanel, and Adobe Marketing Cloud into cloud platforms like AWS and GCP. Extended the platform with AI/ML capabilities — building feature pipelines, customer segmentation and recommendation models, model deployment workflows, and LLM-powered analytics tooling. Collaborated with stakeholders to define data requirements, ensure data quality, and meet project timelines effectively.
- Python
- SQL
- Golang
- Node.js
- AWS
- GCP
- Databricks
- Adobe Marketing Cloud
- Google Analytics 4
- Mixpanel
- scikit-learn
- PyTorch
- LangChain
- MLflow
2019 - 2020
BI & Data Analyst
TransformCo
Analyzed data from various sources to identify trends and patterns, and created reports and dashboards to communicate insights to stakeholders. Developed ETL pipelines to extract, transform, and load data into a data warehouse.
- SQL
- Tableau
- Python
- Snowflake
- Teradata
Expertise
The tools I reach for.
- Languages
- Python
- Go
- Node.js
- SQL
- Cloud & Platforms
- AWS
- Google Cloud
- Azure
- Data Platforms
- Snowflake
- Databricks
- PostgreSQL
- MongoDB
- AI / ML
- scikit-learn
- PyTorch
- LangChain
- MLflow
- Analytics
- Adobe Marketing Cloud
- Google Analytics 4
- Mixpanel
- Tableau
About
A craft, not a checklist.
I design and optimize data pipelines and the systems around them. Across 7 years of professional experience, I have worked with a variety of technologies, including Apache, Python, SQL, Golang, Node.js, AWS, GCP, Databricks, Adobe Marketing Cloud, Google Analytics 4, and Mixpanel. My work began with a deep curiosity about how data drives insights and decisions, and has evolved into a craft I continuously refine. More recently, I have extended that craft into AI and machine learning — designing feature pipelines, training and serving infrastructure, and shipping production ML and LLM-powered systems for marketing analytics. I thrive in collaborative environments and enjoy solving complex data problems to deliver scalable and efficient solutions. Outside of work, I enjoy staying active, exploring new technologies, and reading books.
- Experience
- 7 yrs
- Currently
- DWAO
- Focus
- Data Infrastructure
Contact
Always up for a good
conversation.
Always glad to talk pipelines, ML systems, or LLM tooling — the inbox is open.