Principal Data Architect at Interos

, , -

Full Time

Start Date

Immediate

Expiry Date

19 Jun, 26

Salary

260000.0

Posted On

21 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architecture, Data Engineering, Data Strategy, Database Structures, Data Pipelines, Data Retrieval, Data Lake Architecture, Snowflake, Databricks, Data Security, Data Privacy, Data Migration, Performance Tuning, Data Governance, ML, AI

Industry

Software Development

Description

Role: Principal Data Architect About interos.ai: interos.ai is defining the category of supply chain risk intelligence, building the world’s most trusted and transparent supply chains. Our pioneering platform automates the discovery and continuous monitoring of supply chain risk across every tier — enabling faster, data‑driven threat mitigation and resilience at global scale. As the first and only automated supplier intelligence platform, interos.ai gives organizations real-time visibility into extended supply chains to protect against regulatory risk, unethical labor, cyber threats, and systemic vulnerabilities — all through a single pane of glass. With customers spanning commercial, Federal, A&D, and public sectors, including Global Fortune 500 companies and members of the Five Eyes nations, interos.ai offers a rare opportunity to help shape an early, fast‑growing market that’s transforming global security and economic resilience. At interos.ai, you’ll join a team that’s not afraid to challenge conventions, explore new ideas, and iterate quickly in pursuit of the best solutions. We operate in a space that’s evolving fast, and so are we. Our work is meaningful, the problems we tackle are complex, and the pace requires focus, curiosity, and adaptability. We know interos.ai isn’t the right fit for everyone — and that’s okay. We’re looking for people who are humble in how they collaborate, hungry to succeed, and smart in how they work to solve problems (EQ). People who thrive here are energized by broad exposure and a dynamic scope of work, comfortable navigating ambiguity, open to feedback, proactive in taking ownership, and motivated by making a real impact. If you’re seeking a predictable routine or a highly structured environment, you may find our pace challenging. However, if you’re someone who leans into change, enjoys solving hard problems with great teammates, and wants to contribute to technology that truly matters, you’ll fit right in. We’re excited to meet individuals who bring expertise in their craft, a willingness to experiment, and a mindset grounded in continuous learning. About the Role: As a Principal Data Architect, you will focus on the big picture of interos.ai’s data strategy, developing a cohesive data architecture that supports interos.ai’s long-term vision by designing and developing efficient database structures, data pipelines, standards, and optimizing data retrieval for core product, analytics, and AI purposes. Tech Stack: * Frontend: react.js * Backend: Python fast APIs * Data: Snowflake, Databricks, Gitlab * LLMs: Open-Source models (llama) * Infra: AWS What You’ll Do: * Implement data lake architecture that is aligned with the company’s vision, product, and AI strategy * Collaborate across Engineering, Product, Applied AI, and ML teams to define the strategic data architecture * vision, implement roadmap items, and improve processes * Establish guidelines, controls, and processes to make data available for developing scalable data-driven * solutions for both Analytics and AI * Enforce data ingestion, integration, and access patterns to support real-time, near-real-time, and batch- * based consumer data needs * Investigate system performance to identify areas of improvements, propose architectural updates, assist in * implementation of improvements * Implement security measures to safeguard sensitive data from unauthorized access, ensuring data privacy, * and compliance with relevant regulations * Plan and oversee data migration processes when transitioning to new data platforms or tools * Document data architecture designs, implementations, and best practices * Define, build, and maintain monitoring systems for data pipelines and architecture components * Provide timely resolution to data-related issues and troubleshoot performance bottlenecks * Conduct training sessions for internal teams on data architecture and data engineering best practices, * mentor other data engineers, perform architecture design reviews What You Bring: * Bachelor's or Master's degree in Computer Science or equivalent, with 12+ years of Data Architecture * and/or Data Engineering experience * Proven expertise in designing data platforms for large-scale data and diverse data architectures, including * warehouses, lakehouses, and integrated data stores * Expertise in Snowflake * Experience in using data clean rooms architecture/tools and/or working securely with first-party data in * conjuncture with third-party data * Experience with data security (including PHI and PII), as well as data privacy regulations (CCPA and GDPR) * Ability to manage projects effectively, plan tasks, set priorities, and meet deadlines in a fast-paced * environment Bonus Points For: * You love to build new things and thrive in ambiguity and even failure. You care about innovation. * Entrepreneurial spirit. You are self-directed and innovative; you build trust and are biased towards action in * fast-paced environments. * Exposure to analytics techniques using ML and AI to assist data scientists and analysts in deriving insights * from data What We Offer * Comprehensive health, dental & vision insurance * 401(k) with employer match * Flexible Time Off (FTO) + 10 paid holidays * Opportunity to help shape an early, fast-growing market * A flexible, remote-first work environment that empowers you to perform at your best — wherever you are * An incredible culture built on trust, accountability, and collaboration across time zones and teams Our Core Values At interos.ai, our culture is shaped by three core values that reflect who we are and how we operate as a high‑performing, connected team. Technical Skill We hold a performance‑driven standard across everything we build and deliver. We value depth of expertise, strong judgment, and the ability to turn complex challenges into clear, effective solutions. Excellence is both our expectation and our baseline. Will We show up hungry, humble, and smart. We take ownership, seek growth, and elevate one another through curiosity, accountability, and collaboration. We lean into hard problems with resilience and a commitment to continuous improvement. Thrill We stay connected and bring energy to the work. We believe meaningful relationships, a sense of fun, and celebrating wins together fuel great outcomes. We create space for engagement, connection, and moments that remind us why we love what we do. These values guide how we show up for our partners, our colleagues, and our customers every day. Work Environment, Location, and Travel: This role can be remote-first within the United States, with optional access to our Arlington, VA HQ. Occasional travel may be required depending on business needs. Compensation: Base salary range is $235,000 - $260,000USD based on experience and location. Performance-based annual bonus and stock option may also be included as part of a total compensation package. Equal Opportunity Employer Statement interos.ai is proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees — regardless of race, religion, gender identity, sexual orientation, age, disability, or veteran status. Accessibility & Accommodations We are committed to providing reasonable accommodations for candidates throughout the hiring process. If you need assistance, please contact us at hr@interos.ai.

Responsibilities

The Principal Data Architect will focus on the overarching data strategy, designing efficient database structures, data pipelines, and standards to support the company's long-term vision for product, analytics, and AI purposes. Key duties include implementing data lake architecture, establishing data availability guidelines, enforcing ingestion patterns, and investigating system performance for improvements.