PROCESS // ENGINEERING LIFECYCLE

How we take projects from fragmented data to dependable systems.

Our structured 6-phase engineering process ensures zero surprises. Every milestone is measurable, every delivery is verified against real financial ledgers, and systems are built to run without supervision.

6 — 8 Wks

Average Time to Full Production Delivery

100%

Turnkey Implementation by Engineers

Zero

Hidden Maintenance Overhead for Client

The Six Engineering Phases

Each phase produces tangible, production-ready deliverables with verified checkpoints.

Discover

Understand systems, business requirements, and reporting needs.

0 — 2 weeks

We audit your existing data endpoints, review upstream API quotas, examine current spreadsheets and dashboards, and map out the exact business questions your team needs answered.

Key Phase Deliverables:

Current-State Data Inventory & Source Audit

Core Business Metric Dictionary & KPI Definitions

Technical Feasibility & Quota Assessment Report

Target Architecture Blueprint & Scoping Spec

CLIENT INVOLVEMENTLight: 2-3 technical interviews with stakeholders.

Architect

Design the data architecture, warehouse schema, and integration strategy.

1 — 3 weeks

We design the target warehouse layout, partitioning strategy, staging environments, credential isolation boundaries, and define the data contracts that prevent downstream breaks.

Key Phase Deliverables:

Entity Relationship Diagrams (ERD) & Schema Models

Partitioning, Clustering & Storage Cost Projections

Credential Management & Zero-Trust Security Plan

SLA & Disaster Recovery Runbook Draft

CLIENT INVOLVEMENTMinimal: Review and sign-off on architecture blueprint.

Build

Implement pipelines, transformations, staging tables, and storage.

2 — 6 weeks

We write resilient API clients with token rotation, build stateful delta extractors, implement dbt transformations for currency/timezone normalization, and provision production warehouse tables.

Key Phase Deliverables:

Production Ingestion Connectors with State Watermarking

Automated dbt Transformation Suite with CI/CD Testing

Staging and Production Warehouse Databases

Automated Dead-Letter Queue & Replay Triggers

CLIENT INVOLVEMENTZero: Entirely handled by Novriq Labs engineering team.

Validate

Test data quality, reliability, edge cases, and financial reconciliation.

4 — 7 weeks

We execute historical backfills, test API rate-limit resilience with synthetic throttling, and run 100% financial reconciliation checks comparing warehouse aggregates against source platform receipts.

Key Phase Deliverables:

Multi-Month Historical Backfill & Verification

Financial Reconciliation Audit (Shopify / Stripe vs Bank)

Automated Anomaly Detection & Drift Alarms

End-to-End Stress & Edge-Case Validation Report

CLIENT INVOLVEMENTMedium: Stakeholder validation of sample reporting outputs.

Deliver

Connect the analytics layer, semantic models, and live dashboards.

6 — 8 weeks

We connect Power BI, Tableau, or custom React interfaces to the verified warehouse models, configure Role-Based Access Control, and conduct team handover workshops.

Key Phase Deliverables:

Live Production Dashboards (Power BI / Tableau / React)

Documented Semantic Model with Self-Service Dictionaries

Role-Based Security & Row-Level Permissions Configured

Team Handover Workshop & Recorded Training Walkthroughs

CLIENT INVOLVEMENTHigh: User training, dashboard walkthroughs, final acceptance.

Improve

Monitor, optimize, adapt to new platforms, and extend the system.

Ongoing

We provide continuous 24/7 automated alerting, query performance tuning, proactive adaptation to upstream API version upgrades, and incremental data model extensions.

Key Phase Deliverables:

24/7 Automated Pipeline Health Telemetry & Slack Alerts

Proactive Upstream API Deprecation & Upgrade Migrations

Monthly Query Performance & Cloud Cost Optimizations

Ongoing Data Model Expansion as Business Adds Platforms

CLIENT INVOLVEMENTContinuous: Monthly engineering review and roadmap alignment.

Have a project in mind?

We will walk through Phase 01 Discover with your team, evaluate your current data sources, and outline your target delivery timeline.

Start Discovery