BI / Data Architecture Consultant Needed - Looker, Qlik, AWS vs GCP
I’m looking for an experienced BI / data architecture professional who has hands-on experience with Google Looker, Qlik Sense, and cloud architectures.
The goal is to compare AWS and Google Cloud Platform (GCP) and evaluate whether Google Looker would be the right replacement for Qlik Sense as part of a potential migration to GCP.
This engagement will involve architecture discussion, tool evaluation, and a short hands-on demonstration of Looker.
Current Environment
•AWS cloud environment
• Qlik Sense used for reporting and BI
• Data pulled from legacy systems via ETL
We are considering migration to GCP and are evaluating whether Looker should replace Qlik Sense for reporting and BI.
Topics to Discuss
1. AWS vs GCP for enterprise platforms
o Key advantages and disadvantages
o When GCP makes sense vs AWS
2. Looker in a GCP ecosystem
o Is Looker the natural choice when moving to GCP?
o Can other BI tools work equally well in GCP?
3. Migration considerations
o Effort and complexity of moving from Qlik Sense → Looker
o Common pitfalls in BI tool migration
4. Architecture best practices
o How to designing a tool-agnostic BI architecture
o How to keeping flexibility so can use any BI tool in the future with minimal effort
5. Alternative BI tools
o Other leading reporting / visualization tools besides Looker and Qlik
o How to locate Magic Quadrant for BI/visualization tools in IT Gartner
Hands-On Demonstration (Preferred)
Ideally, the consultant should also be able to:
• Demonstrate Looker in a working environment
• Walk through Looker features and capabilities, including ML functionality
• Guide me through setting up Looker access on my own laptop. I currently have a Google account, but I’m not sure whether that is sufficient to access or set up Looker.
• Guide me to create a simple dashboard example using sample data (e.g., Excel or another data file format)
I’m looking for someone who can provide practical guidance, architectural insight, and hands-on instructions, not just high-level explanations.
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The goal is to compare AWS and Google Cloud Platform (GCP) and evaluate whether Google Looker would be the right replacement for Qlik Sense as part of a potential migration to GCP.
This engagement will involve architecture discussion, tool evaluation, and a short hands-on demonstration of Looker.
Current Environment
•AWS cloud environment
• Qlik Sense used for reporting and BI
• Data pulled from legacy systems via ETL
We are considering migration to GCP and are evaluating whether Looker should replace Qlik Sense for reporting and BI.
Topics to Discuss
1. AWS vs GCP for enterprise platforms
o Key advantages and disadvantages
o When GCP makes sense vs AWS
2. Looker in a GCP ecosystem
o Is Looker the natural choice when moving to GCP?
o Can other BI tools work equally well in GCP?
3. Migration considerations
o Effort and complexity of moving from Qlik Sense → Looker
o Common pitfalls in BI tool migration
4. Architecture best practices
o How to designing a tool-agnostic BI architecture
o How to keeping flexibility so can use any BI tool in the future with minimal effort
5. Alternative BI tools
o Other leading reporting / visualization tools besides Looker and Qlik
o How to locate Magic Quadrant for BI/visualization tools in IT Gartner
Hands-On Demonstration (Preferred)
Ideally, the consultant should also be able to:
• Demonstrate Looker in a working environment
• Walk through Looker features and capabilities, including ML functionality
• Guide me through setting up Looker access on my own laptop. I currently have a Google account, but I’m not sure whether that is sufficient to access or set up Looker.
• Guide me to create a simple dashboard example using sample data (e.g., Excel or another data file format)
I’m looking for someone who can provide practical guidance, architectural insight, and hands-on instructions, not just high-level explanations.
Apply tot his job
Apply To this Job