Data Architect

BravoTech; Dallas (TX); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Bravo Technical Resources Inc. seeks a Data Architect - SAP, Cloud & AI for a hybrid role in Dallas, TX. You will design data platforms, integrate SAP with cloud services, and enable analytics with Snowflake, Power BI, and AI-ready data.

You'll gather requirements, craft architectures and roadmaps, and work across teams to deliver secure, scalable solutions. A strong SAP/data governance background is required.

Qualifications

• 10+ years of data architecture, data engineering, analytics, integration, or related field.
• At least 5 years of SAP experience and 5 years of non-SAP architecture experience.
• Hands-on SAP data, analytics, or integration tech such as SAP BW, SAP BTP, or SAP ERP.
• Strong knowledge of modern data architecture, data modeling, ETL/ELT, cloud platforms, and enterprise integration.
• Ability to translate business needs into secure, scalable technical solutions.

Responsibilities

• Gather requirements and translate them into solution architectures, roadmaps, and reusable data patterns.
• Design and guide data platforms, integrations, pipelines, models, and analytics solutions.
• Connect SAP data and systems with cloud platforms, Snowflake, Power BI, and other tools.
• Prepare trusted, governed data for analytics, ML, and AI agents.
• Recommend point solutions while upholding security, quality, governance, and reuse.
• Collaborate across teams and clearly communicate architecture decisions.

Education

Bachelor's degree in computer science, information systems, engineering, data management, analytics, or related field

Tools

Snowflake

Databricks

Amazon Redshift

SAP BW

SAP BTP Integration Suite

SAP ERP

Power BI

Alteryx

Azure

AWS

SAP HANA Cloud

Job description

Data Architect - SAP, Cloud & AI - Hybrid in Dallas, TX

Help shape modern data solutions that connect enterprise systems, analytics, and AI. In this hands-on architecture role, you'll work across business and technology teams to turn complex needs into secure, scalable solutions - from SAP integrations and cloud data platforms to Power BI and AI-ready data.

What you'll do

• Gather requirements and translate them into practical solution architectures, roadmaps, and reusable data patterns.
• Design and guide modern data platforms, integrations, pipelines, models, and analytics solutions.
• Connect SAP data and systems with cloud platforms, Snowflake, Power BI, and other enterprise tools.
• Prepare trusted, well-governed data for analytics, machine learning, generative AI, and AI agents.
• Recommend point solutions for project needs while supporting enterprise standards for security, quality, governance, and reuse.
• Collaborate with business, engineering, analytics, and other technology teams; communicate design choices clearly.

Required qualifications

• Onsite 2 days per week in Dallas, TX 75202
• 10+ years of experience in data architecture, data engineering, analytics, integration, or a related field.
• At least 5 years of SAP experience and 5 years of non-SAP architecture experience.
• Hands-on experience with SAP data, analytics, or integration technologies, such as SAP BW, SAP BTP Integration Suite, or SAP ERP.
• Strong understanding of modern data architecture, data modeling, ETL/ELT, cloud platforms, and enterprise integration.
• Ability to gather business needs and turn them into secure, scalable technical solutions.
• Experience working across teams and communicating architecture decisions to technical and business audiences.
• Bachelor's degree in computer science, information systems, engineering, data management, analytics, or a related field, or equivalent relevant experience.
• Experience with Snowflake.
• Experience with Databricks, Amazon Redshift, or SAP HANA Cloud is also relevant.
• Experience with Azure; AWS experience is also welcome.
• Familiarity with Power BI, Alteryx, data governance, and enterprise analytics standards.
• Experience designing data services for AI and agent-based solutions, including understanding data needs for retrieval, context, and response traceability.
• Oil and gas experience, especially refining, commercial, logistics, supply chain, trading, or operations.
• Manufacturing experience is also valuable.