Data Engineering Services
Production-grade data pipeline development and data engineering consultancy in the UK — built on Databricks, Snowflake, and Azure with dbt, PySpark, and Delta Lake.
What We Deliver
Data Pipeline Development
End-to-end ETL pipeline development — from raw ingestion through to serving layers. We build pipelines that are testable, observable, and maintainable. ETL pipeline development is at the core of every engagement.
Data Warehouse Design
Dimensional modelling (Kimball), Data Vault 2.0, and medallion architectures. We design schemas that scale with your business and make reporting fast and reliable.
ELT Automation with dbt
dbt consulting services covering model design, testing frameworks, documentation, and CI/CD integration. We convert legacy stored procedures and ETL jobs into clean, versioned dbt models.
Data Quality Frameworks
Automated data quality checks, anomaly detection, and observability pipelines. We implement Great Expectations, dbt tests, and custom validation frameworks to catch issues before they reach the business.
Streaming Data Pipelines
Real-time data pipeline development using Apache Kafka, Azure Event Hubs, Delta Live Tables, and Spark Structured Streaming. From IoT telemetry to financial transaction streams.
Platform Migration
Legacy warehouse and ETL modernisation. We migrate SQL Server, Oracle, and Teradata workloads to Databricks and Snowflake — converting stored procedures to dbt and validating every row.
Our Technology
We work with the leading cloud data platforms and open-source tools. Our dbt consulting services and Databricks expertise are our strongest capabilities.
Databricks
Databricks Lakehouse Platform is our primary compute environment. We design Unity Catalog structures, Delta Lake architectures, and PySpark workloads for production at scale. Our Databricks data engineering projects span from initial platform setup to advanced Delta Live Tables implementations.
Snowflake
Snowflake Data Cloud for analytics-optimised warehousing. We design multi-cluster configurations, data sharing architectures, and Snowpark integrations. Cost governance and query optimisation are standard parts of every Snowflake engagement.
dbt (data build tool)
dbt is central to our transformation layer on every project. We write modular, well-documented, well-tested dbt models. Our dbt consulting services include code reviews, model refactoring, and CI/CD pipeline setup for dbt Cloud and dbt Core.
Our Approach
Modular dbt Models
Staging, intermediate, and mart layers. Every model has a single responsibility and is independently testable.
Automated Testing
Schema tests, custom dbt tests, and data quality assertions built into every pipeline from day one.
CI/CD Integration
GitHub Actions or Azure DevOps pipelines that run dbt tests on every pull request and deploy to production on merge.
Documentation
dbt docs, lineage graphs, and data dictionaries. Your team will understand the platform when we leave.
Engagement Models
Embedded Team
Our engineers work alongside your internal team — integrated into your standups, code reviews, and delivery processes. Ideal for organisations building internal capability.
Standalone Delivery
We own the delivery end-to-end. You define the requirements; we design, build, test, and hand over a documented, production-ready platform.
Advisory
Architecture reviews, code audits, and technical strategy. We assess your current platform and provide a clear recommendation for modernisation.
Why Choose Vamba Data
15+ Years Enterprise Delivery
Our founder has led data engineering projects at Barclays, BP, Expedia, PwC, and Farfetch. We know what production-grade looks like.
Deep Technical Expertise
We are not generalist consultants. Every member of our team is a specialist in data engineering, with hands-on Databricks, dbt, and PySpark experience.
Knowledge Transfer Built In
We document everything and train your team. Our goal is to leave you self-sufficient, not dependent.
Commercial Pragmatism
We choose the right tool for your situation. We will tell you if Databricks is overkill and Postgres is the right answer.
Ready to discuss your data engineering needs? Contact Us