From architecting data pipelines to scaling cloud warehouses for production workloads, Tecla connects you with vetted Snowflake developers who have built and shipped real data systems. We build teams around your stack, your goals, and your delivery pace. Start interviewing in 5 days.
Built data warehouses processing 50TB+ for e-commerce platforms. Specializes in query optimization and cost management. Previously reduced monthly Snowflake spend by 45% through warehouse tuning.
Designed enterprise data warehouses serving 500+ analysts. Expert in star schema design and incremental loads. Migrated legacy systems from Oracle and Redshift to Snowflake.
Built analytics infrastructure for SaaS companies tracking 10M+ events daily. Deep expertise in ELT pipelines and data modeling. Reduced dashboard load times from minutes to seconds.
Transformed raw data into executive dashboards for fintech platforms. Specializes in complex SQL and performance tuning. Strong collaboration with business stakeholders on reporting needs.
Architected real-time data ingestion pipelines using Snowpipe and Streams. Expert in automated workflows with Tasks. Cut data latency from hours to minutes for real-time reporting.
Designed multi-tenant data warehouses for enterprise clients. Specializes in data governance, security, and compliance frameworks. Led Snowflake implementations across 5 Fortune 500 companies.
We match you with qualified Snowflake developers in 5 days on average, not the 42+ days typical with traditional recruiting firms.
Only 3 out of every 100 applicants make it through our vetting process. You get developers who've already proven themselves with production Snowflake warehouses.
Hire Snowflake engineers at 40-60% less than US rates without sacrificing quality or experience level.
Our placements stick. Nearly all clients keep their developers beyond the first year, proving the quality of our matches.
Work with developers in timezones within 0-3 hours of US hours. No more waiting overnight for responses or debugging query issues solo.
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"We needed someone who could optimize our Snowflake warehouse without breaking existing dashboards. Tecla connected us with an engineer who had done exactly that at scale. He cut our monthly bill by 40% in six weeks."
Key result
Hired in 5 days, saved $24K monthly in Snowflake costs
"Traditional recruiting gave us candidates who listed Snowflake on their resume but had never actually designed a data warehouse. Tecla's vetting caught that. The developer we hired knew data modeling and optimization inside out."
Key result
Reduced hiring time from 14 weeks to 7 days
"Our analytics team was drowning in slow queries and confusing data models. The Snowflake developer from Tecla redesigned our warehouse structure and implemented proper modeling. Queries that took 5 minutes now run in seconds."
Key result
Improved query performance by 85%, better data organization
Our Snowflake developers design data warehouses using star schemas, snowflake schemas, or data vault patterns. They work with dimensional modeling, slowly changing dimensions, and fact tables to organize data properly.
Expert-level experience building data pipelines using Snowpipe for streaming ingestion, external tables for raw data, and transformation layers using SQL or dbt. They integrate with Fivetran, Airbyte, or custom Python scripts.
Deep expertise in Snowflake-specific optimizations, clustering keys, materialized views, result caching, and warehouse sizing. They analyze query profiles, identify bottlenecks, and rewrite expensive queries. Your dashboards load faster and your bill goes down.
Our Snowflake developers proactively monitor credit usage, identify expensive queries, implement auto-suspend settings, and right-size warehouses. They set up resource monitors and query tags. They provide architectural reviews to catch cost problems before they compound.
Within 3-5 days, you'll see profiles that match. Every candidate has already passed technical assessments, we've verified they've built production data warehouses, not just completed Snowflake certification courses.
Within 3-5 days, you'll see profiles matched to your tech stack. Every candidate has passed technical assessments, we've verified they've managed production Airflow deployments, not just completed tutorials.
Talk to the candidates who look promising. See how they think through data modeling problems, explain optimization strategies, and whether they'd fit your team's workflow.
Pick your developer and start working together. We handle contracts and logistics so you can focus on getting them up to speed with your data sources and business requirements.
A Snowflake developer builds and maintains data warehouses using Snowflake's cloud platform. Think of them as data engineers who specialize in organizing company data so analysts and data scientists can actually use it, not infrastructure engineers managing servers. The difference from general data engineers? Snowflake developers know the specific features that make Snowflake powerful. They understand virtual warehouses, zero-copy cloning, time travel, data sharing, and how to structure data for fast queries without burning money. These folks sit at the intersection of data engineering, analytics engineering, and database administration. They're not just loading data, they're designing warehouse structures that make sense, writing efficient SQL, and keeping costs reasonable as data grows. Companies hire Snowflake developers when they're migrating from legacy warehouses, scaling analytics infrastructure, or drowning in slow queries and confusing data models. The role grew as more companies realized cloud data warehouses beat maintaining their own databases.
When you hire Snowflake developers, you get data infrastructure that actually supports business decisions. Most companies see query performance improve 5-10x, monthly costs drop 30-50% through optimization, and analysts who can finally self-serve without constant engineering support.
Here's where the ROI becomes obvious. Migrating from an on-premise Oracle warehouse? A Snowflake specialist handles that without losing data or breaking existing reports. Your monthly Snowflake bill keeps climbing and nobody knows why? They identify expensive queries, right-size warehouses, and implement proper clustering.
Analysts complaining they can't find the data they need? Good Snowflake developers design clear data models with proper documentation. Dashboards taking forever to load? They optimize queries, add materialized views, and implement result caching.
Real-time reporting requires streaming data ingestion. Snowflake developers build Snowpipe integrations that load data continuously instead of nightly batch jobs. Your competitors analyze yesterday's data while you're working with the current hour.
Your job description filters candidates. Make it specific enough to attract qualified Snowflake developers and scare off people who just passed a certification exam.
"Senior Snowflake Engineer" beats "Data Wizard" every time. Be searchable. Include seniority level since someone with 2 years SQL experience can't architect an enterprise data warehouse yet.
Give real context. Your stage (seed, Series B, public). Your product (e-commerce analytics, financial reporting, healthcare data). Team size (3-person data team vs. 30+ engineers). Current state (migrating from Redshift, scaling existing Snowflake, building from scratch).
Candidates decide if they want your environment. Help them self-select by being honest about what you're building.
Skip buzzwords. Describe actual work:
Separate must-haves from nice-to-haves. "3+ years building production Snowflake warehouses" means more than "data warehouse experience." Your tools matter, dbt, Fivetran, Looker, Tableau.
Be honest about what you actually need. Data modeling expertise? Query optimization? Pipeline development? Cost management? Say so upfront.
"5+ years data engineering, 2+ years specifically with Snowflake production environments" sets clear expectations. Many strong developers came from Oracle, SQL Server, or Redshift backgrounds. Focus on what they've shipped.
How does your team work? Fully remote with async communication? Role requires explaining data models to non-technical stakeholders? Team values documentation and knowledge sharing?
Skip "team player" and "excellent communication", everyone claims those. Be specific about your actual environment.
"Send resume plus 3-4 sentences about a Snowflake warehouse you designed and what challenges you solved" filters better than generic applications. Set timeline expectations: "We review weekly and schedule calls within 3 days."
Strong candidates explain separation of storage and compute, virtual warehouses that scale independently, and how this enables zero-copy cloning and data sharing. They connect it to real scenarios, running ETL jobs without impacting analyst queries.
Design a data warehouse for a retail company with sales, inventory, and customer data. Walk me through your approach.
This reveals understanding of dimensional modeling. They should discuss fact tables (sales transactions), dimension tables (products, customers, stores), slowly changing dimensions, and grain decisions. Listen for practical considerations like query patterns and update frequency.
Practical candidates check query history for expensive queries, warehouse usage patterns, and credit consumption by user or warehouse. They mention automatic clustering costs, data storage growth, and long-running queries. This shows cost management thinking.
Strong answers investigate what changed, data volume growth, schema changes, new joins. Then optimize: add clustering keys, create materialized views, or restructure the underlying data model. Avoid candidates who immediately suggest "just use a bigger warehouse."
Their definition of success matters. Query performance? Analyst satisfaction? Cost efficiency? Strong candidates explain data modeling decisions, how they handled slowly changing dimensions, and what they learned from production usage.
Experienced developers acknowledge each has strengths. Snowflake excels at SQL analytics with easy scaling. Databricks wins for complex data science workflows. BigQuery offers simpler pricing for Google Cloud shops. This reveals understanding of trade-offs.
Good answers: create clear views that hide complexity, document data models with business definitions, provide example queries, and hold regular office hours. They enable self-service instead of becoming a bottleneck.
What do they focus on? Understanding the actual question behind the request? Clarifying grain and dimensions? Setting expectations on refresh frequency? Good answers mention iterative development and confirming the output meets needs. Listen for collaborative approach.
Neither answer is wrong. But if you're scaling a production warehouse and they only want greenfield work, that's a mismatch. Watch for self-awareness about preferences.
Strong candidates discuss starting with simpler models that work, adding complexity as needs emerge, and when technical debt becomes worth paying down. Avoid candidates who insist on perfect models upfront or never refactor bad designs.
Location changes your budget dramatically without affecting technical ability.
A team of 5 mid-level Snowflake developers costs $625K-$875K annually in the US versus $275K-$400K from LATAM. That's $350K-$475K saved annually while getting the same technical skills, full timezone overlap, and fluent English. These LATAM developers join your standups, debug query issues in real-time, and work your hours. The savings reflect regional cost differences, not compromised quality.
US: $90K-$235K+ depending on seniority. LATAM: $40K-$110K for the same experience levels. That's 52-58% savings.
The difference is cost of living, not skill. LATAM snowflake developers are educated at top universities, work with the same Snowflake features, and have built production data warehouses for US companies.
One senior developer: save $100K-$200K annually. A team of 5: save $500K-$1M total.
Savings come from lower salaries, no US benefits overhead, reduced recruiting fees, and faster hiring. Our 97% retention rate means you're not constantly rehiring.
Post your requirements (Day 1). Review pre-vetted candidates (Days 2-5). Interview matches (Week 1-2). Hire and onboard (Week 2-3). Total: 2-3 weeks versus 6-12 weeks traditionally.
We maintain a vetted pool of 50,000+ developers. No sourcing delays or screening candidates who just passed certification exams. 90-day guarantee ensures technical fit.
Yes. They work with Snowflake's full feature set, virtual warehouses, Snowpipe, Streams, Tasks, data sharing. 80%+ are fluent in English. Many have worked remotely with US companies for years building data warehouses.
Cost reflects regional economics, not skill gaps. A $75K salary in Colombia provides similar quality of life to $175K in San Francisco.
US hiring includes 25-35% benefits overhead, 20-25% recruiting fees, onboarding costs, office overhead, and turnover risk (6-9 months salary).
Nearshore through Tecla eliminates most of these. Developers handle local benefits, recruiting is pre-vetted with transparent rates, remote setup costs less, and 97% retention prevents constant rehiring.
Traditional: 8-16 weeks (sourcing, screening, interviews, negotiation, notice period). Tecla: 2-3 weeks total.
You hire 6-13 weeks faster. While competitors spend months filling roles, you're onboarding someone who starts optimizing your warehouse next week.
Connect with Developers from Latin America in 5 days. Same expertise, full timezone overlap, 50-60% savings.
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