Retail · Zurich

Leading Swiss Retailer — Teradata to Snowflake Migration

The Challenge

Switzerland’s largest retail company, was running its enterprise data warehouse on Teradata. Rising licensing costs, combined with the need for more flexible analytics capabilities, made a migration to a cloud-native platform the strategic priority. But the client couldn’t afford disruption to the data pipelines powering daily retail operations — inventory management, sales analytics, and supply chain reporting all depended on the existing platform.

The challenge wasn’t just technical. Teradata and Snowflake have fundamentally different architectures: distribution keys, join strategies, stored procedures, and workload management all work differently. A naive “lift and shift” would have resulted in poor performance and broken business logic.

Our Approach

DWHPro brought deep expertise in both source (Teradata) and target (Snowflake) platforms — a rare combination in the market. Our consultant holds both Teradata Master and Snowflake SnowPro certifications, ensuring architectural decisions were grounded in production-level knowledge of both systems.

Architecture-First Migration — Conducted a workload analysis of the existing Teradata environment to identify migration priorities and complexity hotspots. Redesigned data models for Snowflake’s architecture rather than blindly converting Teradata SQL. Rebuilt critical ETL pipelines using modern cloud-native tooling.

Data Validation Framework — Implemented automated reconciliation between source (Teradata) and target (Snowflake) to validate row counts, aggregates, and business logic at every stage. Zero-tolerance approach to data discrepancies — every difference investigated and resolved before cutover.

Knowledge Transfer — Worked alongside the client’s internal team throughout, ensuring they could operate and extend the Snowflake platform independently after the engagement.

Results

✓ Successful migration from Teradata to Snowflake — production workloads running on cloud-native platform
✓ Zero data loss across all migrated datasets
✓ Internal team fully trained and self-sufficient on Snowflake post-migration
✓ Modernized data pipeline architecture ready for future analytics and AI workloads

Named references available under NDA — request a reference call.

Technologies: Teradata · Snowflake · Python · ETL/ELT · dbt

Banking · Frankfurt

European Bank — Enterprise DWH Migration

The Challenge

European Bank’s Frankfurt operation relied on a legacy data warehouse that had grown organically over years. The existing architecture couldn’t keep pace with evolving regulatory requirements and increasing data volumes. Performance bottlenecks were impacting reporting timelines, and the cost of maintaining the aging platform was escalating — with no clear path forward.

The bank needed a full DWH migration: not just lifting and shifting data, but redesigning the architecture from the ground up — while maintaining uninterrupted access to critical financial reporting throughout the transition.

Our Approach

DWHPro deployed a senior architect who took end-to-end ownership — from architecture design through lead development to project management. No handoffs between teams, no communication gaps.

Assessment & Architecture Design — Mapped the full existing data landscape: sources, transformations, dependencies, downstream consumers. Identified architectural debt and designed a modern target architecture optimized for regulatory reporting workloads.

Migration & Development — Rebuilt ETL pipelines with modern tooling. Implemented systematic data validation to ensure zero data loss. Managed parallel running of old and new systems during the transition period.

Cutover & Validation — Coordinated production cutover with minimal disruption. Full regression testing across all critical reporting paths. Knowledge transfer to the bank’s internal team.

Results

✓ Complete DWH migration delivered on schedule
✓ Zero data loss — validated across all migration paths
✓ Modern, maintainable architecture replacing years of accumulated technical debt
✓ Single senior consultant covered architecture, development, and project management

Named references available under NDA — request a reference call.

Technologies: Teradata · MS SQL Server · ETL/ELT · Data Vault · Python

Hedge Fund · Connecticut, USA

Global Hedge Fund — Research Data Engineering

The Challenge

One of the world’s largest hedge funds, managing over $100 billion in assets, required specialized data engineering expertise for their research division. The research team’s quantitative models depended on reliable, high-quality data pipelines — any latency or data quality issue could directly impact investment decisions worth billions.

The environment was demanding: extremely high data quality standards, complex multi-source data integration, and a culture of rigorous testing and validation. The client needed a senior engineer who could operate independently at the highest level, with no ramp-up time and no room for error.

Our Approach

DWHPro provided a senior research data engineer with deep expertise in enterprise data platforms and financial data engineering. The consultant integrated directly into the fund’s research team.

Data Pipeline Engineering — Built and maintained production data pipelines serving quantitative research models. Integrated data from multiple financial data providers with strict quality controls. Implemented automated testing and validation frameworks to ensure pipeline reliability.

Data Quality & Governance — Designed data quality checks aligned with the fund’s rigorous standards. Built monitoring and alerting for pipeline health and data freshness. Documented data lineage and transformation logic for audit purposes.

Engineering Excellence — Applied software engineering best practices: version control, code review, automated testing. Contributed to the team’s Python-based tooling and frameworks.

Results

✓ Production data pipelines delivered for one of the world’s most demanding financial institutions
✓ Zero data quality incidents impacting research models
✓ Senior-level delivery from day one — no ramp-up, no hand-holding
✓ Cross-border delivery: Austrian consultant operating seamlessly in a US hedge fund environment

Named references available under NDA — request a reference call.

Technologies: Python · SQL · Data Pipeline Engineering · Automated Testing · Financial Data Integration

Banking · Vienna · 14+ Years

Major European Bank — Regulatory Compliance & Enterprise DW Frameworks

The Challenge

One of Europe’s largest banking groups needed to build and maintain regulatory reporting interfaces for authorities in Austria, Europe, and the United States — including FATCA, CRS, Account Register, capital gains tax (KEST), and Capital Outflow reporting. Failure meant legal consequences, audit findings, and regulatory risk across multiple jurisdictions.

At the same time, the bank’s enterprise data warehouse — processing 5,000+ daily batch jobs across 10+ countries — lacked standardized frameworks. Every new interface was built from scratch, creating inconsistency, duplication, and escalating maintenance costs.

Our Approach

DWHPro embedded a senior architect for what became a 14+ year engagement — the longest client relationship in our history. The scope grew from regulatory interface delivery to enterprise-wide DW architecture leadership.

Regulatory Delivery — Designed and implemented legally required DW interfaces for FATCA (US), CRS (international), Account Register, KEST, and Capital Outflow reporting. Every interface built with auditability, traceability, and zero-restatement reliability.

Enterprise Frameworks — Built standardized core frameworks for historization, surrogate keys, and data quality. These became the bank-wide standard, executed daily by 5,000+ batch jobs. New interfaces could be built 15–25% faster using these repeatable patterns.

Multi-Country Optimization — Redesigned the adjustment framework to support concurrent use by 10+ countries without bottlenecks. Enabled controlled post-load corrections with full audit trails.

Performance Tuning — SQL refactoring and workload stabilization across the enterprise batch environment, achieving 20–60% runtime improvements on targeted high-cost statements.

Results

✓ 14+ year continuous engagement — the longest client relationship in our history
✓ FATCA and CRS reporting delivered under audit pressure with zero restatements
✓ Enterprise DW frameworks adopted as bank-wide standard — 5,000+ daily batch jobs
✓ 15–25% faster implementation of new interfaces through standardized patterns
✓ 20–60% runtime improvements on high-cost SQL statements
✓ Multi-country adjustment framework serving 10+ countries concurrently

Named references available under NDA — request a reference call.

Technologies: Teradata · IBM DataStage · OPC (Tivoli Workload Scheduler) · SQL · Git

Telecommunications · Vienna · 5 Years

Major Austrian Telecom — Billing DW Modernization & Platform Migration

The Challenge

One of Austria’s leading telecommunications providers was processing billions of call detail records daily through a data warehouse that had accumulated years of technical debt. Data quality issues in billing and usage domains were undermining confidence in business reporting. Campaign success analysis lacked the data models needed for actionable insights.

Adding urgency: a new billing system rollout was approaching, and the existing DW architecture wasn’t prepared for the structural changes it would bring. Without careful impact analysis and controlled migration, the transition risked breaking downstream analytics and reporting for the entire business.

Our Approach

DWHPro placed a senior consultant for a 5-year engagement spanning multiple phases of the telecom’s data platform evolution.

Billing & Usage Domain Overhaul — Redesigned and enhanced the billing and usage data warehouse domains, improving data quality and usability for business reporting. Cleaned up years of accumulated technical debt in the core analytical layer.

Campaign Analytics Models — Designed data models enabling efficient campaign success analysis. Marketing teams could now measure ROI on promotions, churn campaigns, and customer acquisition — with data they trusted.

Billing System Migration — Performed comprehensive impact analysis for the rollout of a new billing system across the data warehouse. Mapped every dependency, identified breaking changes, and enabled a controlled transition that protected downstream analytics.

Results

✓ 5-year continuous engagement across multiple platform evolution phases
✓ Billing and usage DW domains modernized — data quality issues eliminated
✓ Campaign analytics models enabled measurable marketing ROI for the first time
✓ New billing system rollout completed without disruption to downstream analytics
✓ Billions of call detail records processed daily with improved throughput and reliability

Named references available under NDA — request a reference call.

Technologies: Teradata · SQL · Enterprise DW Platform · Data Modeling

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Our 5-10 person core team is backed by a strategic Big 4 partnership — we scale to match your programme, with every resource handpicked by us.