SSIS to dbt on Snowflake Migration Case Study

Next Pathway is an Elite Snowflake Partner, trusted by global enterprises to deliver end-to-end modernization, from deep discovery to production cutover.

Case study summary: SSIS to dbt on Snowflake in 6 months

A leading Canadian pension fund decommissioned its legacy SQL Server Integration Services (SSIS) enterprise data warehouse and modernized to dbt on Snowflake in 6 months. Next Pathway's NEXA Platform captured the logic and dependencies across the SSIS estate in its Enterprise Intelligence Graph, giving frontier models the context to automate translation across the estate. 96 SSIS packages became 152 dbt models across two delivery phases, aligned with the client's three-layer Staging, Merge and Target architecture. Apache Airflow replaced SSIS control flows, with the full enterprise audit framework, ETL Helper watermark management and SCD Type 1+ and Type 2+ patterns built in.

Results: SSIS infrastructure fully decommissioned on schedule; enterprise-grade dbt transformations delivered across two phases; improved pipeline maintainability, traceability and governance; a repeatable developer playbook scaling across all packages.

AI readiness: a governed, cloud-native Snowflake and dbt foundation for future EDW expansion, analytics and AI.

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What Next Pathway's Leading Pension Fund Case Study Covers

A leading pension fund modernized its enterprise data warehouse from SSIS to dbt on Snowflake. Next Pathway automated code conversion, modernized ETL pipelines and built a scalable cloud-native platform for future analytics and AI.

Legacy Enterprise Data Warehouse Modernization

The pension fund modernized a legacy SSIS-based enterprise data warehouse, redesigning the data architecture and implementing enterprise-ready governance on Snowflake.

Automated SSIS to dbt Modernization

96 SSIS packages became 152 dbt models with Next Pathway's NEXA Platform. Apache Airflow replaced SSIS orchestration, and a QA framework built in the first phase accelerated delivery in the second.

Cloud-Native Foundation for Analytics and AI

A scalable Snowflake data platform with modular dbt transformations, enterprise audit capabilities and modern orchestration now supports advanced analytics, AI initiatives and future data platform growth.

1 Billion+

Lines of legacy code translated

160+

Migrations and modernizations delivered

80%

Faster than manual and semi-automated approaches

SSIS to dbt on Snowflake: frequently asked questions

Answers drawn from the leading pension fund case study.

How long did the SSIS to dbt on Snowflake modernization take?

6 months. The pension fund decommissioned its legacy SSIS-based enterprise data warehouse and modernized to dbt on Snowflake across two delivery phases, BSAR and BSAD, both completed on schedule.

How many SSIS packages were converted to dbt models?

96 SSIS packages were converted into 152 dbt models: 59 packages and 95 models in the BSAR phase, and 37 packages and 57 models in the BSAD phase. Next Pathway's NEXA Platform captured the logic and dependencies across the SSIS estate in its Enterprise Intelligence Graph, giving frontier models the context to automate translation across the estate.

What dbt architecture was used on Snowflake?

A three-layer dbt architecture of Staging, Merge and Target layers, aligned with the client's enterprise framework. It integrates the full enterprise audit framework and ETL Helper watermark management, and implements SCD Type 1+ and Type 2+ patterns across complex model types.

How was SSIS orchestration replaced?

Apache Airflow replaced SSIS control flows for orchestration, alongside the modernization of SSIS ETL logic into dbt Core transformations on Snowflake.

How did the project meet enterprise governance requirements?

Next Pathway used a hybrid translation approach that elevated automated output to the client's enterprise dbt standards, built a QA framework in the first phase and applied it to the second, and supported testing and user acceptance through go-live.

What Industry Analysts Say

Rob Enderle

ENDERLE GROUP

"Next Pathway is providing a solution that accelerates the migration process, giving organizations a faster route to realizing value from their data."

Eric Kavanagh

THE BLOOR GROUP

"SHIFT Cloud enables a remarkably swift and robust transition from traditional data warehousing to the cloud."

What a structured Snowflake modernization covers

A successful Snowflake modernization requires a clear plan across four disciplines.

Discovery and dependency mapping

Every code object, ETL pipeline and data dependency is identified and documented before modernization begins, so hidden complexity surfaces early and the program stays on schedule.

Code translation and modernization

Legacy SQL, stored procedures and ETL pipelines are converted into optimized, Snowflake-native workloads. Automated translation removes manual rework and covers the full estate.

Validation and functional parity

Every modernized workload is validated against the legacy source to confirm data accuracy and functional equivalence. Parity is proven before cutover.

Production cutover planning

Cutover needs a defined plan covering resources, rollback decisions and business sign-off. Teams that plan cutover from the start move faster and with greater confidence.