ELT Pipelines for Scalable Data Integration
Transforming fragmented enterprise data into trusted, analytics-ready assets with cloud-native solutions
Our Data Pipeline & ETL Consulting Services
We help teams transform raw data into value — efficiently, scalably, and in sync with your business goals. Whether you’re modernising legacy ETL or building your first analytics stack, we deliver flexible, cloud-native ELT pipelines tailored to your architecture and analytics needs.
- Multi-source data ingestion frameworks
- Modular dbt development for scalable transformations
- Real-time and batch data processing
- Cloud-native warehousing (Snowflake, BigQuery, Redshift, Databricks)
- Data governance, versioning & observability
- Workflow orchestration and monitoring
Ready to Explore the Potential of Modern Data Pipelines?
Whether you’re consolidating fragmented data or scaling enterprise analytics, we’ll help you unlock value through robust, cloud-native ELT solutions.
Let’s discuss how Data Pipelines can work for you.
Unified Data Platform for Cross-Channel Analytics
Design and implementation of a robust ELT framework to centralise, transform, and serve multi-source business data using Databricks, dbt, and cloud-native tools.
Client & Goal Overview
Client Type
Retail Technology Platform (Omnichannel SaaS)
Challenge
The client operated in a fast-paced retail environment with data scattered across multiple operational systems (e-commerce, in-store POS, CRM, inventory, and marketing platforms). Slow reporting cycles, inconsistent metrics, and a lack of visibility across channels were limiting business agility. The objective was to centralise and standardise data delivery for analytics through an automated, scalable ELT pipeline.
Our Role
We designed and delivered a cloud-native ELT architecture combining Databricks and dbt on Google Cloud Platform (GCP). The solution ingested, transformed, and modelled multi-source data for near real-time decision-making, enabling consistent, governed insights across business units.
Project Journey & Results
Project Scope
- Consolidated data from 5+ sources (Salesforce, Shopify, Oracle ERP, Google Ads, in-store POS) into a central GCS landing zone.
- Leveraged Databricks for scalable ingestion and preprocessing with Auto Loader and Delta Lake.
- Built modular dbt models for transformation, testing, documentation, and lineage tracking.
- Delivered analytics-ready datasets to BigQuery for reporting, dashboarding, and machine learning workloads.
- Implemented scheduling, monitoring, and governance controls for reliability and compliance.
Technical Stack
- Ingestion: Databricks Auto Loader + Google Cloud Functions
- Transformation: dbt Cloud with modular SQL and Git integration
- Storage: Delta Lake on GCS
- Warehouse: Google BigQuery
- Orchestration: Databricks Workflows
- Monitoring: dbt artifacts, Datadog alerts
- Access Control: IAM roles, service accounts, and row-level policies in BigQuery
Results
- Centralised fragmented data into one source of truth across departments.
- Enabled self-service reporting with daily data freshness.
- Improved data model transparency and stakeholder trust via dbt documentation.
🟧 Cut reporting cycle from 2 days to 1 hour.
🟧 Reduced manual data prep tasks by 85%.
🟧 Achieved 99.5% pipeline success rate with automated testing and alerts.
Ready to streamline your data workflows?
✓ Discover how modern ELT pipelines with Databricks and dbt reduce friction and increase insight readiness. ✓ Book a strategy consultation to explore use cases, architecture options, and expected ROI. Have a question or idea?
Explore Other Projects
Whether it's transforming data into strategic insight, deploying intelligent systems, or building scalable AI solutions, these projects reflect the diversity and depth of our consultancy work. Explore how we've partnered with clients to solve complex problems, unlock value, and drive innovation across sectors.
