Data Platform Engineering

We design, build, and optimize end-to-end data platforms — from raw source ingestión to analytics-ready warehouses. Our expertise spans Snowflake, Azure SQL, PostgreSQL, and modern ELT/ETL tooling. Whether you are migrating from legacy systems, building from scratch, or optimizing an existing platform for cost and performance, we deliver production-grade data infrastructure that scales with your business.

What We Deliver

Data warehouse design and implementation on Snowflake, Azure Synapse, or PostgreSQL
ETL/ELT pipeline development with Python, dbt, Airflow, or Azure Data Factory
Data lake and lakehouse architectures using Delta Lake, Iceberg, or Parquet
Real-time streaming with Kafka, Azure Event Hubs, or Snowpipe
Data quality frameworks, testing, and monitoring
Legacy database migration (SQL Server, Oracle, MySQL to Snowflake/PostgreSQL)
Performance optimization, query tuning, and cost reduction

Technologies We Use

Snowflake

Cloud data warehouse — our primary platform for analytics workloads

Azure SQL / Synapse

Microsoft Azure ecosystem — SQL Database, Synapse Analytics, Data Factory

PostgreSQL

Open-source relational database — ideal for transactional and hybrid workloads

dbt

Data transformation framework — SQL-first, version-controlled, tested

Python

Core language for ETL, automation, data quality, and orchestration

Why dataqbs for Data Platform Engineering

With 20+ years engineering data systems across healthcare, fintech, mining, and e-commerce, we have seen every failure mode and know what works at scale. We are not a staffing agency — we are hands-on engineers who write the SQL, build the pipelines, and optimize the queries ourselves.

Certified: SnowPro Core, SnowPro Data Engineer, Azure DP-900, AI-900
Full-stack: from raw data ingestión to executive dashboards
Remote-first delivery with async communication and documentation
Fluent in English, Spanish, and German

Industries We Serve

Healthcare & Life Sciences Fintech & Banking Mining & Energy E-commerce & Retail Insurance Education & EdTech

Frequently Asked Questions

What is the typical timeline for a data platform project?

Most projects run 2-6 months depending on scope. A focused migration or warehouse build typically takes 8-12 weeks. We deliver in iterative sprints so you see value early — not just at the end.

Do you work with our existing team or replace them?

We augment your team, not replace it. Our model is embedded engineering — we work alongside your data engineers, transfer knowledge, document everything, and build systems your team can maintain after we leave.

Can you help us migrate from SQL Server to Snowflake?

Yes — database migration is one of our core strengths. We have migrated T-SQL stored procedures, SSIS packages, and complex ETL to Snowflake + dbt + Python. We handle schema conversion, data válidation, and performance benchmarking as part of the project.

Ready to get started?

We design, build, and optimize end-to-end data platforms — from raw source ingestión to analytics-ready warehouses.

Get in touch

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