What data engineering services do you offer?

I offer comprehensive data engineering services including real-time data pipeline development, trading algorithm creation, cloud data architecture, ETL/ELT implementation, and business intelligence solutions.

What technologies do you specialize in?

I specialize in Python, SQL, Apache Kafka, Apache Spark, AWS cloud services, PostgreSQL, Docker, Kubernetes, and various data processing frameworks for building scalable data solutions.

Do you work with financial data and trading systems?

Yes, I have solid experience developing trading algorithms, processing financial market data in real-time, and building trading systems with good performance.

What is your typical project timeline?

Project timelines vary based on complexity, ranging from 2-4 weeks for simple integrations to 3-6 months for comprehensive data platform implementations. I provide detailed estimates during initial consultations.

Let's Build SomethingReliable Together

Ready to discuss your data engineering challenges?

"Whether it's real-time pipelines, trading systems, or ML in production — let's talk about building infrastructure that doesn't fail when it matters most."

< 24hrs

Response Time

3+ Years

Data Engineering

98%+

System Reliability

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Multiple Ways to Connect

Choose the communication method that works best for your project timeline and complexity

For urgent projects or quick questions. Available during business hours (UTC-4)

+58 412 3020280

Response: Usually within 2-4 hours

Email

For detailed project discussions, proposals, and technical specifications

datawithjose@outlook.com

Response: Within 24 hours

Location & Time

Based in Caracas, Venezuela. Available for remote collaboration worldwide

UTC-4 (Venezuela Time)

Mon-Fri: 9AM-6PM

Remote projects worldwide

Prefer a Different Platform?

I'm also available on professional networks and can accommodate your preferred communication method

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Tell Me About Your Data Challenge

Whether you need real-time pipelines, trading systems, or ML in production — share your project details and I'll get back to you with insights and next steps.

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