Fullstack Data and Platform Engineer (m/f/d)

Join us!:
We are looking for a Fullstack Data & Platform Engineer (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 unstructured data and more lakehouse-style capabilities on AWS. We work hands-on across Python-based data services, pipelines, asynchronous integrations, AWS infrastructure, and SQL/PostgreSQL-based processing.
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 strongly hands-on engineering role focused on building and operating reliable data infrastructure for internal product and platform use cases.

What can you expect?:
Build and operate the shared data infrastructure
Build and maintain the data infrastructure that powers the platform. Design and implement ingestion flows, ETL/ELT pipelines, and shared processing patterns that enable reliable and scalable data usage across the company.
Work on structured and evolving data foundations
Help evolve the platform’s structured data foundation around PostgreSQL while supporting the path toward S3-backed and lakehouse-style capabilities over time.
Build event-driven and asynchronous integrations
Design and implement asynchronous and event-driven workflows using AWS-native patterns such as Amazon EventBridge. Ensure integrations are reliable, resilient, and maintainable in production.
Ensure trust and reliability in platform data
Implement data quality checks, validation rules, freshness controls, and monitoring to ensure semantic, API, and AI use cases can rely on trusted data inputs.
Support reusable data access
Help build curated datasets and shared access layers that support semantic models, API products, and AI-powered features.
Contribute to platform operations and delivery
Implement CI/CD for data workflows, maintain infrastructure as code, and support production readiness through monitoring, troubleshooting, and continuous improvement.
Work closely across the team
Collaborate closely with the Data & Platform Architect, Semantic / Analytics Engineer, and AI engineers to ensure the platform data foundation is reliable, reusable, and aligned with downstream needs.
Explore and establish modern engineering methods
Work actively with spec-driven development and AI-assisted engineering workflows. Help establish practical ways of working that improve quality, speed, and maintainability.

What should you bring along?:
Strong hands-on data engineering skills
Strong practical experience with Python and SQL, and solid knowledge of PostgreSQL, including query writing, performance tuning, and production-grade data processing.
Experience with pipelines and transformation
Experience building data ingestion pipelines and ETL/ELT workflows in production environments. Experience with dbt or similar transformation tooling is expected.
Orchestration and workflow reliability
Experience with orchestration and pipeline scheduling, and a solid understanding of how to build reliable, maintainable data workflows.
Event-driven and distributed systems thinking
Experience with event-driven architecture, ideally including Amazon EventBridge or similar systems. Good understanding of idempotency, retries, dead-letter handling, and resilient distributed processing.
Cloud and platform engineering mindset
Experience with AWS services for data, compute, monitoring, and security, as well as CI/CD, infrastructure as code, and deployment automation.
Data quality and operational ownership
Experience with data quality, validation, observability, and operational reliability. You are comfortable owning data workflows in production, not just implementing them.
Collaborative and pragmatic communication
You work well with architects, semantic engineers, and upstream solution teams, communicate clearly, and help turn requirements into robust technical solutions.
AI-assisted and spec-driven mindset
You are comfortable working with structured specifications, clear contracts, and AI-assisted development workflows as part of day-to-day engineering.
Fullstack ownership mindset
You bring strong specialization in data and platform engineering 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 Airflow, Dagster, or similar orchestration tools
• Experience with S3-based analytical storage, query engines, and lakehouse-style evolution
• Experience with Terraform or CDK
• Experience with AWS services such as SQS, Lambda, and Step Functions
• Experience with semantic platforms, reusable data products, or analytics engineering
• Experience with unstructured data ingestion and hybrid architectures
• 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