Data Warehouse & Business Intelligence Agency Needed

LearnTastic is looking for an experienced data engineering / BI agency or small technical team to help us build the foundation of a centralized Data Warehouse and Business Intelligence platform for our four e-commerce brands: AHCA, ACCA, Learntastic, and ACLS. Individual freelancers should not apply. We are specifically looking for an agency or team with multiple technical capabilities. Project Overview Our transactional data is primarily stored in AWS Aurora and exceeds 100GB+, with additional data across marketing, affiliate, payment, and experimentation platforms. We want to create a centralized analytical data platform using: AWS Aurora + APIs → S3 → Amazon Redshift Serverless → dbt → Power BI The goal is to create a reliable analytical source of truth while ensuring that reporting workloads do not impact our production databases. Data Sources The project will involve integrating data from: AWS Aurora – AHCA, ACCA, Learntastic, ACLS Stripe – payments, refunds, disputes, fees, payouts Google Ads Meta Ads Microsoft Ads AWIN LinkConnector VWO Scope of Work The selected agency will help with: 1. AWS Data Warehouse Foundation Review and validate the proposed architecture Set up / configure S3 and Amazon Redshift Serverless Establish appropriate RAW, STAGING, CORE, and DATA MART layers Ensure production Aurora workloads remain isolated Recommend and implement appropriate ingestion methods such as Zero-ETL or AWS DMS/CDC where applicable 2. Data Ingestion Develop or configure initial ingestion pipelines for priority data sources. The solution should support API-based ingestion and retain raw data in S3 where appropriate for auditing and reprocessing. 3. dbt & Data Modeling Create an initial dbt project with: Staging models Core dimensional models Data marts Automated data-quality tests Documentation Version control / GitHub integration Expected warehouse entities include areas such as: Customers Orders Products Brands Campaigns Affiliates Payments Refunds Disputes Advertising spend Experiments 4. Marketing & Attribution Build a foundation for connecting marketing data across: Google Ads Meta Ads Microsoft Ads AWIN LinkConnector Where available, we need to support identifiers such as: Customer ID Visitor ID Session ID GCLID MSCLKID FBCLID UTM parameters 5. Stripe / Financial Reconciliation Create the foundation for tracking: Order → Payment → Refund → Dispute → Fee → Net Revenue The model should support reconciliation of payments, refunds, disputes, fees, and unmatched transactions. 6. Power BI Create the initial Power BI reporting foundation. The planned dashboards include: Executive Overview Marketing Performance Finance & Reconciliation Sales Performance Experimentation The initial engagement can focus on establishing the data model, connections, and initial dashboard structure, with additional dashboards developed in subsequent phases if required. Data Quality & Security The solution should include basic validation for: Duplicate records Missing/orphan transactions Failed or stale data feeds Reconciliation differences Data transformation errors The implementation should follow AWS security best practices, including least-privilege IAM and appropriate access restrictions. PCI-sensitive PAN/card data must not be stored in the warehouse. What We Need From Your Agency Please provide: Your agency/company profile Examples of similar AWS + Redshift + dbt + Power BI projects Experience with e-commerce data warehouses Experience integrating Stripe and advertising APIs Your proposed technical approach What you can realistically deliver within the $1,000 budget Estimated timeline Team members who would work on the project Any additional costs or assumptions