About Us
IntegrityNext, a global leader in supply chain sustainability software, stands at the forefront of corporate sustainability and compliance. Since 2016, businesses have trusted IntegrityNext to simplify ESG compliance, reduce risks, and address critical challenges like due diligence, decarbonization, and sustainability reporting. With over 500 customers and 2 million suppliers across 190 countries, IntegrityNext is transforming supply chains into engines of transparency and sustainable growth. For more information, visit www.integritynext.com.
We are an equal opportunity employer and do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We welcome applicants from all backgrounds and strive to create an environment where everyone feels respected and heard. Join us in our mission to build a more equitable and inclusive world.
Join us!
We are looking for a Data & Platform Architect (m/f/d) to strengthen our team.
At IntegrityNext, we are building a shared AI and data platform on AWS on top of our supply chain and product compliance platform. This platform will power semantic data access, BI, APIs, and agentic product experiences.
Our platform is initially centered on PostgreSQL-backed structured data and will evolve toward support for unstructured data and more lakehouse-style capabilities on AWS. We work hands-on across Python-based platform services, data pipelines, SQL/PostgreSQL-based data architecture, and AWS-based integrations , while collaborating closely with Java-based product systems .
We work according to the principle "You build it, you run it" : platform capabilities are owned end-to-end, from design and implementation to operational responsibility in production. We also follow spec-driven development and actively use AI-assisted engineering tools such as Claude Code, Cursor, and similar tools.
This is a hands-on architect role with a strong engineering focus . We expect roughly 70% hands-on engineering work and 30% architectural guidance, design reviews, and technical alignment .
What can you expect?
Design and build the shared data platform
Take ownership of the shared data and platform foundation. Design and implement data models, pipelines, storage patterns, access layers, and integration boundaries that support reliable and scalable reuse across the company.
Shape reusable business meaning in data
Define canonical data models, reusable business entities, semantic structures, and access patterns that support BI, APIs, and AI use cases. Ensure data is modeled in a way that preserves business meaning and enables consistent downstream consumption.
Contribute directly in implementation
This role is not limited to architecture and guidance. You will actively build platform capabilities, work on complex engineering tasks, pair with engineers on implementation, and help turn platform concepts into production-ready systems.
Define contracts and integration patterns
Work closely with solution teams to define and enforce data contracts, schema standards, and integration patterns. Help create stable, reusable interfaces between domain systems and the central platform.
Balance architecture and delivery
Drive architecture decisions across data, platform, and integration topics. Find the right balance between long-term maintainability and pragmatic delivery, and translate business and platform needs into robust technical designs.
Build platform foundations for the future
Guide the evolution of the platform from a PostgreSQL-based foundation toward support for unstructured data and lakehouse-style capabilities. Help shape future API access patterns for curated data products and shared platform capabilities.
Support production readiness
Review designs and code, support monitoring and troubleshooting, and continuously improve reliability, maintainability, and operational robustness.
Explore and establish modern engineering methods
Work actively with spec-driven development and AI-assisted engineering workflows. Help evaluate and establish practical ways of working that improve quality, speed, and team effectiveness.
What should you bring along?
Strong Data Architecture And Modeling Experience
Several years of experience designing and operating data platforms in production environments, with strong expertise in data modeling, domain-oriented design, reusable access patterns, and semantic structures.
Strong hands-on engineering capability
Strong practical experience with Python and SQL , as well as solid knowledge of PostgreSQL , including schema design, query performance, and production-grade data modeling. You are comfortable building systems yourself, not only guiding others.
Semantic and reusable data design
Experience defining canonical models, shared business entities, reusable metrics, semantic layers, and canonical business data models that support analytics, APIs, and AI use cases.
Platform And Integration Experience
Experience designing data pipelines, integration layers, shared platform access patterns, and data contracts across systems. Good understanding of AWS services for compute, storage, networking, security, and monitoring.
Event-driven and cloud-native thinking
Experience with event-driven architecture, ideally including Amazon EventBridge or similar technologies, as well as CI/CD, infrastructure as code, and deployment automation.
Clean and maintainable engineering practices
You write readable, maintainable, and well-tested systems, and you can explain architectural and design decisions clearly and pragmatically. You are also comfortable reviewing designs and code and improving consistency and long-term quality.
Confidence in evolving environments
You are comfortable working in areas with uncertainty, evaluating new tools and approaches, and helping define practical standards as the platform matures.
Collaborative and pragmatic communication
You communicate clearly, challenge assumptions constructively, and work effectively with product, domain, and engineering teams. You are comfortable collaborating with Java-based solution teams and defining clean integration boundaries.
AI-assisted and spec-driven mindset
You are comfortable working with structured specifications, clear interfaces, schema standards, schema evolution practices, and AI-assisted development workflows as part of day-to-day engineering.
Fullstack ownership mindset
You bring deep specialization in data and platform architecture while being willing to contribute across adjacent layers when needed to deliver end-to-end outcomes.
Fluent English
You can work effectively in an English-speaking environment.
Nice to have
- Experience with lakehouse-style architectures and analytical data platforms
- Experience with unstructured data and hybrid structured/unstructured architectures
- Experience with dbt, orchestration tools, and modern ELT/ETL practices
- Experience with Terraform or CDK
- Experience with REST/GraphQL APIs, service boundaries, and multi-tenant platform design
- Experience with data quality, lineage, and observability
- Experience in multi-team SaaS environments
What do we offer?
Purpose & Impact
- A role with real meaning that is both enjoyable and impactful
- The opportunity to make a sustainable contribution through your work
- Attractive compensation as part of a growing company
Attractive Benefits
- 30 days of paid vacation
- EGYM Wellpass membership to support your work-life balance
- Flexible working models to better balance work and personal life
Modern Work Environment & Flexibility
- Inspiring office spaces in the heart of Munich
- Flexible remote work from home or anywhere within Germany
Great Team
- A professional, welcoming, and highly motivated team
- Collaboration at eye level with an open feedback culture
- An environment where people support each other and grow together
Flat Hierarchies & Ownership
- Short decision-making paths and real opportunities to shape things
- Freedom to contribute and implement your own ideas
- A high level of ownership and responsibility
