Senior Data Engineer / Architect

Confidential; Austin (TX); On-site; USD 140,000 - 180,000; Full time

Job summary

Confidential in Austin is hiring a Senior Data Engineer / Data Architect to help build a next-generation data and analytics platform. The role blends hands-on engineering with architectural leadership, focusing on a data warehouse–first, AI-centric operating model.

You will partner with the Head of Data & Analytics, own technical decisions, and shape how data is acquired, modeled, governed, and productized across use cases, including AI-enabled capabilities.

Qualifications

• Senior-level experience designing and building modern data platforms.
• Strong hands-on data engineering experience.
• Experience with cloud data warehouses, ELT, data modeling, and production data operations.
• Ability to translate architectural decisions into working products.
• Experience turning architecture into reusable data products.
• Comfortable collaborating with data, analytics, application, and business leaders.
• An accomplished individual contributor seeking broader technical leadership.

Responsibilities

• Own system and technical architecture for a data warehouse first, AI-centric operating model.
• Co-own data architecture and product design with Head of Data & Analytics.
• Lead AI-enabled capabilities within data products.
• Build reusable capabilities ahead of requests.
• Work hands-on to implement architectural decisions.

Skills

Data architecture

Data engineering

Cloud data warehouses

ELT patterns

Data modeling

AI-enabled data

Hands-on implementation

Stakeholder collaboration

Job description

This position is not eligible for visa sponsorship or sponsorship transfers.

Position Summary

The Senior Data Engineer / Data Architect will be a core member of the team building a next-generation data and analytics platform and advancing a data warehouse first, AI-centric operating model.

Working in close partnership with the Head of Data & Analytics and the broader data team, this person will own system and technical architecture and co-own data architecture—while remaining hands-on in building the platform. They will shape how data is acquired, integrated, modeled, governed, and productized across operational, revenue, and strategic use cases.

This is a product-building role, not a requirements-taking role. We expect the team to understand the business, anticipate what it will need next, and build reusable capabilities ahead of individual requests.

As part of their technical architecture ownership, this role will lead the build of AI-enabled capabilities into our data products and operating model, while also using AI to accelerate development. The objective is practical leverage: combining trusted data, strong engineering, and AI to expand what the team and business can accomplish.

Purpose

Own the system and technical architecture for a data warehouse first, AI-centric operating model, while co-owning data architecture and product design with the Head of Data & Analytics and broader data team. Build the technical foundation that turns trusted data into reusable operational, analytical, and AI-enabled capabilities—and strengthen the team’s ability to evolve that foundation over time.

• Senior-level experience designing and building modern data platforms, with strong hands-on data engineering experience.
• Deep involvement in system, technical, and data architecture—contributing to architectural decisions, evaluating tradeoffs, and translating those decisions into working implementations.
• Ready to take the next step from influencing architecture to leading it, with the judgment, curiosity, and ambition to earn increasing architectural ownership as the platform and team mature.
• Strong experience with modern cloud data warehouses, ELT patterns, data modeling, orchestration, testing, and production data operations.
• Demonstrated ability to move fluidly between design and hands-on implementation—turning architectural concepts into durable, scalable products.
• Experience supporting multiple data consumption patterns, including analytics, operational workflows, APIs/integrations, and emerging AI use cases.
• Practical experience building AI-enabled data or application capabilities—or the technical foundation and curiosity to lead their development.
• Strong judgment around architectural tradeoffs, including real-time vs. batch, direct integration vs. warehouse-mediated patterns, and speed vs. long-term maintainability.
• Comfortable working as a technical peer with data, analytics, application, integration, and business leaders.
• Strong documentation, collaboration, and knowledge-sharing discipline, with a bias toward creating reusable capabilities rather than one-off solutions.
• An accomplished individual contributor looking for a larger arena—motivated by the opportunity to help build the platform, establish the standards, shape how the team operates, and grow into broader technical leadership.

Ideal Background

• Senior-level experience designing and building modern data platforms, with strong hands-on data engineering experience and exposure to system, technical, or data architecture decisions.
• Strong experience with modern cloud data warehouses, ELT patterns, data modeling, orchestration, testing, and production data operations.
• Demonstrated ability to turn architectural decisions into working products—comfortable moving between design, hands-on implementation, and ongoing platform evolution.
• Experience designing data solutions that support multiple consumption patterns, including analytics, operational workflows, APIs/integrations, and emerging AI use cases.
• Practical experience building AI-enabled data or application capabilities—or the technical foundation and curiosity to lead their development.
• Strong judgment around architectural tradeoffs, including real-time vs. batch, direct integration vs. warehouse-mediated patterns, and speed vs. long-term maintainability.
• Comfortable working as a technical peer with data, analytics, application, integration, and business leaders.
• Strong documentation, collaboration, and knowledge-sharing discipline, with a bias toward creating reusable capabilities rather than one-off solutions.
• An experienced individual contributor ready for greater ownership and technical leadership—someone who has successfully delivered complex data solutions and is ready to expand their scope into architecture, technical direction, and how a data team operates.
• Motivated by the opportunity to build something, establish the standards, and grow as a technical leader as the platform, product, and team mature.