Engineering
Modern data infrastructure built for AI at scale
Without sound data architecture, every AI initiative is built on sand. We design and implement modern, scalable data platforms that can support both analytical workloads and AI/ML at enterprise scale — from ingestion to serving.
What We Deliver
Core capabilities
Our Data Architecture & Engineering practice covers the full spectrum — from advisory through implementation and ongoing operations.
Data Lakehouse Architecture
Unified storage and compute on Databricks, Apache Iceberg, or Delta Lake — combining the flexibility of lakes with warehouse reliability.
Data Mesh Implementation
Domain-driven data ownership models with federated governance, self-serve infrastructure, and product-thinking for data.
Real-Time Data Pipelines
Streaming ingestion and processing on Apache Kafka, Azure Event Hubs, and Databricks Structured Streaming.
Cloud Data Warehouse
Snowflake, Azure Synapse, Google BigQuery, and Amazon Redshift — architecture, implementation, and optimization.
Data Migration & Modernization
Legacy data warehouse migration to cloud-native platforms with zero-downtime cutover strategies.
Feature Stores & Vector Databases
AI-ready infrastructure including feature stores (Feast, Tecton) and vector databases (Pinecone, Weaviate, pgvector).
Our Approach
How we work with you
Architecture Assessment
Review current data infrastructure, identify scalability bottlenecks, and define target-state architecture.
Platform Design
Design the end-to-end data platform blueprint — ingestion, storage, transformation, serving, and governance layers.
Implementation & Migration
Build pipelines, migrate data, and validate with parallel-run testing before production cutover.
Optimize & Handover
Performance tuning, cost optimization, documentation, and knowledge transfer to your engineering team.
Proven Results
What clients achieve
These are real outcomes from engagements we've delivered — not marketing projections.
- Query performance improved 10–50x on analytical workloads post-migration
- Data pipeline latency reduced from hours to minutes with real-time streaming
- Cloud infrastructure costs reduced 30–45% through optimization and right-sizing
- AI/ML teams unblocked within 4 weeks of feature store deployment
Ready to get started?
Book a free 30-minute discovery call. We'll map your specific situation to a practical path forward — no generic pitch decks.