Data platforms that
scale with the business.

Challenge

No cloud-compatible data modeling tool existed for the stack. Development lacked standardization for code tracking, environment management, documentation, and orchestration.

Solution

Built a Python-native framework with automated column-level lineage, dependency graphs, self-documenting BI datasets, catalog sync, and full CI/CD integration.

Result

Validated the modeling pattern at scale. Successfully transitioned the organization to sqlMesh when a mature open-source option emerged - the framework made migration seamless.

Challenge

Scheduling logic fragmented across Airflow, Step Functions, and Dagster. Each had its own monitoring, error handling, and operational semantics.

Solution

Engineered a high-performance job scheduler in Rust deployed on ECS. Unified all scheduling into a single system with consistent alerting and error handling.

Result

Single pane of glass for all pipeline operations. Reduced on-call burden and improved reliability across the board.

Challenge

Advertisers needed precise inventory availability across many dimensions. Predictions had to be accurate enough to commit campaigns against and communicate with confidence.

Solution

Built an ML pipeline with 500-segment clustering and per-cluster regression. Model statistics revealed a mean-based approach produced identical results - replaced the system with SQL queries.

Result

Same accuracy, fewer anomalies, dramatically simpler operations. A deliberate simplification driven by data, not compromise.

Challenge

4,000+ advertising pipelines across throttled vendor APIs (20K requests/day cap). Just loading configuration consumed 12,000 calls. Manual management was unsustainable.

Solution

API wrapper with incremental state caching reduced startup calls from 12,000 to under 100. Dynamic queue management using historical job durations prevented resource overloading.

Result

Fully self-healing system. Automated detection, retries, and escalation freed the team entirely from routine pipeline management.

Challenge

80+ associates spent up to 90 minutes daily downloading the same report from a mainframe. Bi-weekly consolidation took two analysts nearly a week.

Solution

Automated mainframe extraction via event-driven pipelines. Built a custom platform with real-time database sync, standardized workflows, and persistent tracking.

Result

Eliminated 90 min/day for 80+ users. Bi-weekly reporting went from a week to real-time. Became the foundation for unified operational finance.

Challenge

Legacy orchestration tool supported git but had no way to continuously deploy merged changes. Cross-environment object IDs embedded in XML didn't translate between environments.

Solution

Built a deployment pipeline with custom ID resolution and XML transformation logic that the vendor's own API couldn't handle.

Result

Git merges automatically propagated to test and production. Eliminated manual deployments and direct environment changes entirely.