Maintain and extend collection of demo data pipelines
Our company has built a tool using Python to monitor data pipelines and services.
To test and demonstrate the tool's capabilities, we have a set of demo playground pipelines with various simple tasks...
- data ingest
- ETL
- model training
- model deployment
The pipelines demonstrate the ability to work with a wide variety of common data science and analytics resources:
- AWS / GCP services (deployment with Pulumi)
- AWS S3 / GCP Cloud Storage
- APIs
- database operations
We want to keep extending and refining these demos as we continue to build features for our product:
- dbt
- Airbyte
- Databricks
- Snowflake
- etc
We'd like to find someone willing to take on a few tasks per week to help maintain and expand these demos and docs.
The budget is limited to start, with opportunity to renegotiate after 2 weeks. You are encouraged to use cursor and Claude Sonnet 3.5. We are very flexible on scheduling.
Example tasks we have for the upcoming few weeks:
- Establish an API Gateway (v1) for public access to an AWS Lambda, secured with rate limiting and a secret key
- Create a copy of an existing AWS Lambda pipeline with an event-driven architecture instead of a single python script
- Create a copy of an existing AWS Lambda model training script as a Databricks notebook
- Create a copy of an existing AWS Lambda pipeline using Airbyte
- Create a copy of an existing AWS Lambda pipeline using dbt
- Create a copy of an existing AWS Lambda pipeline using AWS Glue
- Create a sample dataset and load it into Snowflake
- Create a sample dataset and load it into Postgres (Neon)
- Update an existing pipeline task so that it will fail (timeout) every Saturday
- Update an existing pipeline task so that it will fail (bad API key) every Wednesday
If this is of interest, please introduce yourself and share
- a desired weekly budget,
- desired number of hours, and
- which of the above tasks you'd expect to be able to accomplish in a first week given ~4 hours (half a day
To test and demonstrate the tool's capabilities, we have a set of demo playground pipelines with various simple tasks...
- data ingest
- ETL
- model training
- model deployment
The pipelines demonstrate the ability to work with a wide variety of common data science and analytics resources:
- AWS / GCP services (deployment with Pulumi)
- AWS S3 / GCP Cloud Storage
- APIs
- database operations
We want to keep extending and refining these demos as we continue to build features for our product:
- dbt
- Airbyte
- Databricks
- Snowflake
- etc
We'd like to find someone willing to take on a few tasks per week to help maintain and expand these demos and docs.
The budget is limited to start, with opportunity to renegotiate after 2 weeks. You are encouraged to use cursor and Claude Sonnet 3.5. We are very flexible on scheduling.
Example tasks we have for the upcoming few weeks:
- Establish an API Gateway (v1) for public access to an AWS Lambda, secured with rate limiting and a secret key
- Create a copy of an existing AWS Lambda pipeline with an event-driven architecture instead of a single python script
- Create a copy of an existing AWS Lambda model training script as a Databricks notebook
- Create a copy of an existing AWS Lambda pipeline using Airbyte
- Create a copy of an existing AWS Lambda pipeline using dbt
- Create a copy of an existing AWS Lambda pipeline using AWS Glue
- Create a sample dataset and load it into Snowflake
- Create a sample dataset and load it into Postgres (Neon)
- Update an existing pipeline task so that it will fail (timeout) every Saturday
- Update an existing pipeline task so that it will fail (bad API key) every Wednesday
If this is of interest, please introduce yourself and share
- a desired weekly budget,
- desired number of hours, and
- which of the above tasks you'd expect to be able to accomplish in a first week given ~4 hours (half a day