You will get AWS Data Pipeline Health Check with ETL Performance Review
Project details
This project provides a focused health check of an existing AWS data pipeline to identify reliability, performance, and data quality issues.
It is designed for teams who already have ETL pipelines built using AWS Glue, Apache Spark, SQL, or related tools and want a second opinion before investing more time or cost.
What sets this project apart is its fixed scope and practical output. Instead of generic advice, I review one pipeline end-to-end and provide clear, actionable findings based on real-world data engineering practices.
This health check covers:
• Pipeline architecture and data flow
• ETL logic and transformation efficiency
• SQL query performance and potential bottlenecks
• Data quality, validation gaps, and failure risks
• High-level cost and scalability concerns
You will receive a written summary report with prioritized recommendations that you can directly use for planning fixes or improvements. This service focuses on analysis and guidance only — no production changes or implementation are included.
It is designed for teams who already have ETL pipelines built using AWS Glue, Apache Spark, SQL, or related tools and want a second opinion before investing more time or cost.
What sets this project apart is its fixed scope and practical output. Instead of generic advice, I review one pipeline end-to-end and provide clear, actionable findings based on real-world data engineering practices.
This health check covers:
• Pipeline architecture and data flow
• ETL logic and transformation efficiency
• SQL query performance and potential bottlenecks
• Data quality, validation gaps, and failure risks
• High-level cost and scalability concerns
You will receive a written summary report with prioritized recommendations that you can directly use for planning fixes or improvements. This service focuses on analysis and guidance only — no production changes or implementation are included.
Data Tool
SQLWhat's included $25
These options are included with the project scope.
$25
- Delivery Time 2 days
- Number of Revisions 1
- Number of Graphs/Charts 0
- Number of Scenarios 1
- Number of Model Variations 0
Optional add-ons
You can add these on the next page.
Fast 1 Day Delivery
+$10
Additional Scenario
(+ 1 Day)
+$10Frequently asked questions
About Roy
Data Engineer
Howrah, India - 12:24 am local time
I work primarily with AWS Glue, Apache Spark, Hadoop, SQL, Python, and shell scripting to design reliable ETL workflows and improve existing data pipelines.
My typical work includes:
• Building and maintaining batch ETL pipelines using AWS Glue and Spark
• Writing Python-based transformation logic and optimized SQL queries
• Handling data ingestion from relational databases and flat files into Amazon S3
• Performing pipeline health checks to identify reliability, performance, and cost issues
• Adding data validation, reconciliation, and quality checks
• Creating shell scripts for automation, monitoring, and log analysis
• Reviewing existing pipelines to improve stability and scalability
I prefer clearly defined, fixed-scope work such as pipeline reviews, ETL fixes, SQL optimization, and small automation tasks. My focus is on clean execution, practical solutions, and clear communication.
If you need help improving an existing data pipeline or building a simple, reliable ETL process, feel free to reach out.
Steps for completing your project
After purchasing the project, send requirements so Roy can start the project.
Delivery time starts when Roy receives requirements from you.
Roy works on your project following the steps below.
Revisions may occur after the delivery date.
Collect Pipeline Details
Review the provided pipeline information to understand the data flow, tools, and current concerns.
Pipeline Analysis
Analyze the ETL logic, SQL queries, performance, reliability, and data quality aspects of the pipeline.