Platforms teams can trust

We design schemas, ingestion, and access patterns so analysts, ML features, and customer-facing apps read consistent definitions. Work includes dbt or SQL transformations, incremental models, and documentation that stays close to the code.

AI-ready data

• Chunking, deduplication, and ACL-aware indexing for retrieval workloads.
• PII classification, masking, and row-level security aligned to policy.
• Backfills and CDC strategies that keep vectors and features fresh as sources change.
• Cost-aware partitioning and clustering for heavy fact tables.

Integration

We implement resilient connectors with rate-limit awareness, webhook receivers, and reconciliation jobs so finance and operations see the same numbers your APIs expose.

How it Works

• Source – to-curated data models with naming and ownership conventions
• Data quality checks and anomaly alerts on critical pipelines
• Semantic layer or metrics definitions consumable by BI and LLM tools
• Embedding and feature stores wired to training and online serving paths

Qualifications & Requirements

• Inventory of systems of record and acceptable replication lag by domain
• Data governance contacts for retention, residency, and access reviews
• Warehouse or cloud project with budgets agreed for storage and compute