SQL & data engineering
The foundation under reliable analytics: pipelines that run, warehouses that scale, and one governed source of truth — across Redshift, SQL Server, Azure, Snowflake, and Databricks.
Data infrastructure that holds up
ETL / ELT development
Ingestion, transformation, and scheduled refresh against warehouse and cloud sources — resilient to the late, messy files your systems actually produce.
Warehouse & model design
Star schemas, source-of-truth views, and medallion architectures designed for the reports you need — not textbook diagrams.
Query optimization
CTEs, window functions, indexing, and refactoring that turn hour-long jobs into minutes.
Data cleaning & integration
Dedup logic, validation rules, and reconciliation across systems that have never agreed with each other.
The data problems underneath your reporting problems
Five systems, five versions of the truth
We consolidate sources into governed views so every downstream report pulls the same numbers.
The nightly load breaks weekly
Fragile manual processes get rebuilt as monitored, documented pipelines with failure alerting.
Queries crawl as data grows
Optimization and modeling fixes that scale with your data instead of fighting it.
One person knows how it works
Everything we build is documented and trained on — the system survives turnover.
Build the foundation once, properly.
Tell us where your data lives and we will sketch the architecture on the first call.