Marketing Analytics Platform Development

Build a secure MMM (Marketing Mix Modeling) platform

Goal: Design and deliver an Solution of a marketing analytics platform (like “Forvio”) with two deployment options:

SaaS / Lake-Write – we can store client data in our data lake and run everything in our cloud.

Data-in-Place / Zero-Retention – we must not store client data. We read from the client’s warehouse/lake, run transforms + training, produce the model, but no client data is saved in our platform. (All model artifacts/serving remain in our cloud.)

We need a senior freelancer who can lead solution architecture, project planning, and hands-on development to solution.

Scope of Work

A. Architecture & Security

Design end-to-end architecture for both options (AWS first; Azure second).

Define zero-retention controls (no data persisted), client-owned keys, private networking, and confidential compute path (AWS Nitro Enclaves / Azure Confidential VMs) for encryption-in-use.

Create an Integration Contract (JSON) so our app works in any client cloud without code changes (storage/warehouse/queue/secrets endpoints).

B. Data layer & Connectors

Configure Fivetran (and SFTP/DB replication where needed) to land data to:

SaaS: our S3/warehouse, or

Data-in-Place: client S3/ADLS/Snowflake/Synapse.

Define canonical data contracts (spend, sales, price, promo, reach/freq, search volume) and implement data-quality checks (Great Expectations or similar).

C. Processing, Modeling & Serving

Build ETL adapters (pushdown SQL/Snowflake/Spark) that run either in our cloud (SaaS) or in client cloud (Data-in-Place).

Implement MMM training (Bayesian adstock + saturation; pooling; search bias correction; calibration hooks).

Package training + transforms into a sealed Runner container (black box) that runs next to client data and exports only a model bundle (parameters/curves; no rows).

Stand up what-if & budget optimization APIs in our cloud using the model bundle (no client data required).

D. Orchestration, CI/CD, and Observability

Pipelines: Step Functions/EventBridge (AWS) and ADF/Logic Apps (Azure).

IaC: Terraform or CloudFormation/Bicep for one-click installs in client accounts.

Observability: CloudWatch/Azure Monitor dashboards, alerts; evidence pack per run (attestation, key-use logs, no-write audit).

E. Docs & Handover

Architecture diagrams, runbooks, security design, onboarding guide, and project plan/Gantt with milestones.

Deliverables (MVP)

Dual-mode architecture (SaaS + Data-in-Place) with diagrams and security controls.

Integration Contract JSON + Preflight tool (permissions/network/schema checks).

ETL adapters + data contracts + DQ tests.

Runner container (sealed) + model bundle validator (allow-list).

Deployed what-if/optimizer API in our cloud.

IaC for both options; monitoring dashboards; evidence pack samples.

Tech Stack (experience desired)

Cloud: AWS (required), Azure (nice).

Data: Snowflake/S3/ADLS, Redshift/Synapse, Fivetran, SFTP/DB replication.

Compute: SageMaker/ECS/EKS or AzureML/AKS; Spark/Glue/Snowpark.

Security: IAM/Key Management (AWS KMS / Azure Key Vault), PrivateLink/Private Endpoints, Nitro Enclaves / Confidential VMs.

IaC & DevOps: Terraform/CFn/Bicep, CI/CD, container hardening.

Modeling: MMM (Bayesian preferred), calibration/experiments, optimizer/what-if APIs.