Data Engineer, Python ETL Developer, or Sports Data Engineer
Budget: ₹12,500 – ₹37,500 INR
Project Title: End-to-End Horse Racing AI Data Platform
I am building an AI-powered horse racing analytics platform focused on Indian race clubs. I need an experienced developer/data engineer to build the entire backend data infrastructure.
Scope of work:
1. Data acquisition (legal and authorized sources only)
* Identify official, licensed, or publicly available data sources
* Create automated data collection pipelines
* Build daily data update mechanisms
2. Historical data collection
Collect and maintain historical data for:
* Bangalore
* Hyderabad
* Mysore
* Chennai
* Mumbai
* Pune
* Kolkata
* Other available Indian race clubs
3. Data fields required
Horse details:
* Horse name
* Horse age
* Sex
* Owner
* Stable
* Equipment changes
Race details:
* Race date
* Race club
* Race number
* Distance
* Race class
* Prize money
* Number of runners
* Track condition
* Surface type
Performance details:
* Finishing position
* Beaten margin
* Race timing
* Weight carried
* Draw number
* Odds
People details:
* Trainer
* Trainer changes
* Jockey
* Jockey changes
Advanced analytics fields:
* Days since last run
* Track specialist score
* Distance specialist score
* Form score
* Consistency score
* Weight advantage score
* Trainer performance score
* Jockey performance score
4. Database
Build a scalable PostgreSQL database with proper relationships and indexing.
5. API development
Develop secure APIs to provide:
* Today’s races
* Horse profiles
* Historical performance
* AI-ready datasets
* Search functionality
6. Dashboard requirements
* Race analyzer
* Horse comparison
* Trainer comparison
* Jockey rankings
* Daily insights
* Statistics dashboard
7. AI preparation
Prepare data for machine learning models and prediction engines.
8. Technical stack preferred
* Python
* FastAPI
* PostgreSQL
* Docker
9. Deliverables
* Source code
* Database schema
* API documentation
* Deployment guide
* Data pipeline documentation
Important: The solution must use only legal and authorized data sources. No bypassing security, unauthorized access, or violating website terms of service.
I am building an AI-powered horse racing analytics platform focused on Indian race clubs. I need an experienced developer/data engineer to build the entire backend data infrastructure.
Scope of work:
1. Data acquisition (legal and authorized sources only)
* Identify official, licensed, or publicly available data sources
* Create automated data collection pipelines
* Build daily data update mechanisms
2. Historical data collection
Collect and maintain historical data for:
* Bangalore
* Hyderabad
* Mysore
* Chennai
* Mumbai
* Pune
* Kolkata
* Other available Indian race clubs
3. Data fields required
Horse details:
* Horse name
* Horse age
* Sex
* Owner
* Stable
* Equipment changes
Race details:
* Race date
* Race club
* Race number
* Distance
* Race class
* Prize money
* Number of runners
* Track condition
* Surface type
Performance details:
* Finishing position
* Beaten margin
* Race timing
* Weight carried
* Draw number
* Odds
People details:
* Trainer
* Trainer changes
* Jockey
* Jockey changes
Advanced analytics fields:
* Days since last run
* Track specialist score
* Distance specialist score
* Form score
* Consistency score
* Weight advantage score
* Trainer performance score
* Jockey performance score
4. Database
Build a scalable PostgreSQL database with proper relationships and indexing.
5. API development
Develop secure APIs to provide:
* Today’s races
* Horse profiles
* Historical performance
* AI-ready datasets
* Search functionality
6. Dashboard requirements
* Race analyzer
* Horse comparison
* Trainer comparison
* Jockey rankings
* Daily insights
* Statistics dashboard
7. AI preparation
Prepare data for machine learning models and prediction engines.
8. Technical stack preferred
* Python
* FastAPI
* PostgreSQL
* Docker
9. Deliverables
* Source code
* Database schema
* API documentation
* Deployment guide
* Data pipeline documentation
Important: The solution must use only legal and authorized data sources. No bypassing security, unauthorized access, or violating website terms of service.