Real-Time SQL Data Pipeline Support
Budget: ₹2,500 – ₹0 INR
I’m setting up a small-scale SQL-based data pipeline dedicated to real-time analytics. The data you’ll work with lives in our existing relational databases and needs to land—clean, modeled, and query-ready—in GBQ (Google BigQuery).
Your industrial experience as a Data Engineer or seasoned SQL Developer will be key. I’d love to collaborate closely in Pune if you’re local, but I’m open to remote help as long as communication is smooth and response times are quick.
Scope of work
• Design the end-to-end ELT flow that moves data from source databases into BigQuery with minimal latency.
• Write efficient, well-documented SQL that handles incremental loads, deduplication, and basic data quality checks.
• Configure scheduling and monitoring so we’re alerted to any pipeline breaks or performance drifts.
• Leave me with concise deployment notes so I can operate and extend the pipeline myself.
Acceptance criteria
1. Industry Hand on in Data Engineering Job
2. Source-to-target mapping document and commented SQL scripts.
If you’ve built similar data pipelines before and can back it up with examples, let’s talk.
Your industrial experience as a Data Engineer or seasoned SQL Developer will be key. I’d love to collaborate closely in Pune if you’re local, but I’m open to remote help as long as communication is smooth and response times are quick.
Scope of work
• Design the end-to-end ELT flow that moves data from source databases into BigQuery with minimal latency.
• Write efficient, well-documented SQL that handles incremental loads, deduplication, and basic data quality checks.
• Configure scheduling and monitoring so we’re alerted to any pipeline breaks or performance drifts.
• Leave me with concise deployment notes so I can operate and extend the pipeline myself.
Acceptance criteria
1. Industry Hand on in Data Engineering Job
2. Source-to-target mapping document and commented SQL scripts.
If you’ve built similar data pipelines before and can back it up with examples, let’s talk.