Logic pursuits
Logic pursuits
dbt Services
We help you turn fragmented data pipelines into a reliable source of business intelligence.
Your data platform is only as trustworthy as the transformation layer running on top of it.
Most organizations invest heavily in modern data platforms, only to discover that the data flowing through them cannot be trusted. Legacy ETL tools, custom SQL, inconsistent metric definitions, and limited testing create reporting discrepancies that slow decisions and undermine confidence in analytics.
As a Certified dbt Labs Partner, we help organizations modernize this transformation layer through structured assessment, migration, implementation, optimization, and enablement. Having migrated 400+ complex ETL jobs across Snowflake, Databricks, BigQuery, and Redshift, we build governed, testable, and analytics-ready transformation layers that reduce maintenance costs, improve data reliability, and give reporting, analytics, and AI initiatives the trusted foundation they need to scale.
How we
make it possible
Every successful dbt engagement follows the same underlying logic: inventory the existing pipeline estate before committing to a migration or build plan, co-design the dbt architecture with the analysts and engineers who will work in it daily, and stay embedded through deployment rather than stepping back at go-live.
- Current stack and pipeline inventory across all ETL and transformation tooling
- dbt maturity scorecard benchmarked against industry standards
- Prioritized modernization and implementation roadmap
- Architecture blueprint and POC scoping
- Delivered as a 3-to-4-week assessment workshop
- Full pipeline inventory and dependency mapping across SAP DS, Informatica, SSIS, Talend, or custom SQL
- Migration grouping by complexity and domain
- Incremental, parallel-run migration with validated cutover
- Proven playbook with 400+ ETL jobs migrated across enterprise environments
- Phased rollout across 12 to 20 weeks
- dbt Cloud environment setup and governance framework
- Data standards, naming conventions, and style guide
- Testing framework design: schema tests, business logic tests, and custom tests
- CI/CD design and DevOps integration
- Staging, Intermediate, and Mart layer modelling and implementation
- Delivered across 6-to-8-week sprints
- Query profiling and bottleneck audit across all dbt models
- FinOps dashboards and cost monitors for warehouse usage tied to dbt workloads
- Semantic layer design and MetricFlow implementation for governed, AI-ready metrics
- Data contracts, observability tooling, and governance hardening
- Delivered as a 5-to-8-week quick-win engagement
- Training program: SQL analyst to analytics engineer pathway
- dbt governance standards, style guides, and coding conventions
- Internal Centre of Excellence setup with operating model, data product ownership framework, and role definitions
- Pair programming and code reviews embedded throughout delivery
- Ongoing retainer support and model maintenance
Multiplying outcomes for your business
Readiness and Maturity
Gain a clear understanding of your transformation landscape, modernization priorities, and the steps required to build a scalable, governed dbt environment with confidence.
Legacy ETL to dbt Migration
Replace costly, difficult-to-maintain ETL tools with a modern transformation layer that improves reliability, reduces technical debt, and lowers long-term operating costs.
dbt Project Setup and Build
Establish a governed, testable, and analytics-ready transformation framework that gives your teams greater confidence in the quality and consistency of business data.
Performance and AI Readiness
Improve model performance, control warehouse costs, and create trusted metrics that support analytics, reporting, and AI initiatives at scale.
Analytics Engineering COE
Build internal analytics engineering capability through training, governance, and operating models that help your teams own, extend, and continuously improve the platform.
Helping your leaders accelerate decisions
Impact tailored for your industry
Migrate legacy ETL to a governed dbt and Snowflake transformation layer that improves data reliability and reporting performance. Ensure the right outcomes with an approach has been proven across large-scale cruise line operations.
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Build audit-ready, testable dbt transformation pipelines for financial reporting, GL analytics, and reconciliation workflows. Leverage consistent metric definitions, documented lineage, and automated testing to reduce compliance risk while helping finance teams close faster with greater confidence.
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Build SOX-compliant dbt transformation layers for rights, royalties, and content revenue data. Support near real-time financial reporting across global streaming operations with governed metrics, documented lineage, and automated data contracts.
Modernize finance, procurement, and operations reporting with modular dbt pipelines that replace manual SQL and legacy ETL scripts. Use tested, documented dbt models to improve reporting accuracy, strengthen data consistency, and reduce ongoing maintenance overhead.
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Migrate legacy SAP, Informatica, or SSIS pipelines to dbt across Snowflake or Databricks. Reduce operational overhead while supporting audit, regulatory, and reporting requirements across complex financial environments with modular, testable transformation layers.
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Integrate supply chain, production, and sales data through a governed dbt transformation layer. Replace fragile custom ETL with tested, documented dbt models that improve data reliability, reduce manual maintenance, and support operational and commercial reporting.
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Results you can count on
ETL jobs migrated to dbt
SAP DS jobs converted
Annual licensing cost eliminated
Reduction in maintenance costs
Increase in data throughput
Reduction in query response time
