How Korvato Built a Data Engineering Team in 10 Days and Shipped Their Analytics Platform 3 Months Early
Korvato needed experienced data engineers to build a real-time financial analytics pipeline processing millions of daily transactions. US data engineers at the required seniority were scarce and expensive. Odesa placed 3 specialists in 10 days, saving Korvato $195K annually and accelerating their platform launch by a full quarter.
The Challenge
Korvato’s financial analytics platform required engineers who understood both modern data stack technologies (Snowflake, dbt, Airflow) and financial domain knowledge — a rare combination in any market. The company had open positions for 3 months with only 2 candidates making it past the first interview round. Neither accepted the offer.
Meanwhile, their enterprise clients were waiting on pipeline features that required the data team to be at full capacity. Every month of delay meant deferred revenue and the risk of losing early adopter customers to competitors who were moving faster.
Why Korvato Chose Odesa
Korvato’s VP of Engineering had previously worked with offshore teams on two continents and had a strong preference for Eastern European engineers based on his experience with timezone overlap, communication quality, and technical depth. He evaluated 4 staffing providers and chose Odesa because Val personally understood the Snowflake/dbt ecosystem and could technically vet candidates beyond surface-level screening.
The candidates Val sent us knew Snowflake better than people we'd interviewed who listed it as their primary skill on LinkedIn. That level of vetting is why we didn't need to look anywhere else.
The Solution
Val conducted a 90-minute technical requirements session with Korvato’s engineering lead to map out the exact data stack, query patterns, and domain requirements. Sourcing began the same day.
| Role | Experience | Tech Stack | Days to Place |
|---|---|---|---|
| Senior Data Engineer | 9 years | Snowflake dbt Python Airflow | 3 days |
| Data Engineer | 6 years | Snowflake SQL Spark AWS | 4 days |
| Analytics Engineer | 5 years | dbt Looker Python Snowflake | 3 days |
The Results
The 3-person Odesa data team shipped Korvato’s real-time analytics pipeline within 90 days — a full quarter ahead of the original projection based on US-only hiring. The pipeline now processes 4M+ daily transactions with sub-second query performance.
Annual cost comparison: the equivalent US team would cost approximately $495K (salary + benefits). The Odesa team costs $300K annually. Savings: $195K per year, every year, with the same quality output and full US timezone overlap during East Coast business hours.
Key Takeaways
Korvato’s experience demonstrates the value of working with a staffing partner who understands your specific technology stack. Generic recruiters struggle to differentiate between a “data engineer who’s used Snowflake” and a “Snowflake-native data engineer who can optimize your warehouse from day one.” That distinction saved Korvato weeks of onboarding time and resulted in production-quality code from week two.
The 2-week risk-free trial was validated within the first week. Korvato’s engineering lead reported that all three developers were writing production-ready dbt models by day 5.
Need data engineers?
Talk to Val about staffing your data team with Snowflake, dbt, and analytics specialists.
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