Phoenix - Your AI AssistantData Pipeline Build – Automated ETL Workflows
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4 days
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What you get with this Offer
I will design and build a fully automated data pipeline for your AI or analytics project — covering data ingestion from your source systems, transformation and cleaning logic, and loading to your target destination (database, data warehouse, or flat file output) — running on a scheduled basis so your AI models and dashboards always have access to fresh, clean, correctly formatted data without manual intervention. Manual data preparation that your team repeats daily or weekly is one of the most expensive and error-prone processes in any data-driven business, and it is almost always fully automatable.
The pipeline is built in Python using pandas, SQLAlchemy, and scheduling via Airflow, Prefect, or simple cron depending on your infrastructure, with configurable source connectors (REST API, database, CSV/FTP, cloud storage), transformation logic tailored to your data and downstream requirements, error handling and alerting for failed runs, and run logging for audit and debugging. The pipeline is containerised with Docker for consistent deployment across environments.
This service suits data teams, analysts, and ML engineers who are currently preparing data manually for recurring AI model retraining, dashboard refresh, or reporting cycles and want that process automated reliably.
The pipeline is built in Python using pandas, SQLAlchemy, and scheduling via Airflow, Prefect, or simple cron depending on your infrastructure, with configurable source connectors (REST API, database, CSV/FTP, cloud storage), transformation logic tailored to your data and downstream requirements, error handling and alerting for failed runs, and run logging for audit and debugging. The pipeline is containerised with Docker for consistent deployment across environments.
This service suits data teams, analysts, and ML engineers who are currently preparing data manually for recurring AI model retraining, dashboard refresh, or reporting cycles and want that process automated reliably.
What the Freelancer needs to start the work
Please describe your data sources (APIs, databases, files, or cloud storage), your transformation requirements, your target destination, your required refresh frequency (hourly, daily, weekly), your infrastructure environment, and any existing pipeline code or documentation I should build on or replace.