Specialist / Manager Data and AI Engineering
Munich
Full-time
Permanent employee
Your Mission
You will be the technical backbone of Armira’s emerging Data & AI function, responsible for building and maintaining the firm’s internal data infrastructure and AI-powered workflows. This is a two-pillar builder role: you will be responsible for (1) designing and implementing Armira’s central data warehouse, ingestion pipelines, data models, and reporting layer, and (2) building AI- and LLM-powered internal tools and workflows that support the investment team’s day-to-day processes, leveraging existing APIs, agent frameworks, and workflow automation tools. Depending on your background, you may lean more toward one pillar initially – what matters is the ability and drive to work across both.
Your Responsibilities
Pillar 1: Data Warehouse & Infrastructure
Pillar 2: AI Workflow Development & Internal Tooling
We expect you to leverage well-established, cloud-native tools and to keep the architecture simple, well-documented, and maintainable, so that another engineer could understand and operate key pipelines within a short onboarding period. We are not optimising for cutting-edge custom architectures, but for pragmatic, robust solutions. The expected tech stack aligns with well-established tools in data engineering:
- Architect, build, and maintain a centralised data warehouse consolidating fragmented data sources across the firm
- Design ETL/ELT pipelines to ingest, transform, and structure data from market databases, deal pipeline sources, and internal systems
- Implement data quality frameworks and governance standards appropriate for a regulated financial services environment
- Build dashboards and reporting tools to enable self-service analytics for the investment team
Pillar 2: AI Workflow Development & Internal Tooling
- Design and build AI-powered workflows (e.g., LLM integrations, n8n/Make automation) to automate and enhance deal sourcing, due diligence support, and internal reporting workflows
- Develop internal tools and applications using LLM APIs, integrating with existing systems (CRM, document management, communication platforms)
- Prototype, test, and iterate on AI-powered workflows, translating business requirements into technical solutions under the guidance of senior leadership
- Stay current with the rapidly evolving AI/LLM ecosystem and evaluate and recommend new tools and approaches for implementation
We expect you to leverage well-established, cloud-native tools and to keep the architecture simple, well-documented, and maintainable, so that another engineer could understand and operate key pipelines within a short onboarding period. We are not optimising for cutting-edge custom architectures, but for pragmatic, robust solutions. The expected tech stack aligns with well-established tools in data engineering:
- Data Warehouse: e.g., Snowflake, Fabric
- Cloud: Preferred Azure
- Transformation & Orchestration: dbt / Airflow
- Visualisation: Tableau / Power BI
- Programming: Python, SQL
- AI/LLM: OpenAI, Anthropic APIs; agent frameworks (LangChain, MCP, etc.); workflow automation (n8n, Make)
Your Profile
Required Qualifications:
- Degree in Computer Science, Data Science, Engineering, or a related quantitative field
- 2+ years of professional experience (Specialist: 2–5 years; Manager: 5+ years) in data engineering, software development, or applied data science
- Ideally, at least one end-to-end build of a data product, internal tool, or data platform in a professional setting (e.g., designing a data model, building pipelines, and putting dashboards or an internal application into production)
- Strong programming skills in Python; solid experience with SQL and modern data stack tools (e.g., Snowflake, dbt, Airflow)
- Experience with cloud platforms (AWS, GCP, or Azure)
- Familiarity with LLM APIs (OpenAI, Anthropic, or similar) and willingness and experience to build AI-powered workflows (e.g. n8n, make.com)
- Ability to work independently, manage ambiguity, and deliver end-to-end solutions
- Fluent in English; German proficiency is a strong plus
- Experience in or exposure to financial services, consulting, or private equity
- Familiarity with agentic AI frameworks (LangChain, CrewAI, or similar) and/or workflow automation platforms (n8n, Make)
- Experience with data visualisation tools (Tableau, Power BI, or similar)
- Understanding of PE workflows (deal sourcing, due diligence, reporting) as context for building effective internal tools
- Track record of building data products or internal tools in a smaller-team environment
Why us?
What We Offer:
- Unique opportunity to build a function from scratch at a leading DACH investment holding
- Deep exposure to the investment team and PE deal-making: you will sit in on deal discussions, portfolio reviews, and strategy meetings, building a genuine understanding of how private equity works and developing your own professional network in the industry
- Competitive compensation
- Munich-based role with work-from-home options, combined with a collaborative, entrepreneurial team culture
- High autonomy with clear career growth path as the data function scales
- Learning and development budget for conferences, courses, and certifications
About us
Armira is a Munich- and London-based investment holding with a truly differentiated DNA driven by entrepreneurial long-term capital. Backed by a unique capital base of entrepreneurs and entrepreneurial families, we invest with a long-term mindset and a highly flexible mandate. Across our three investment strategies, we partner with exceptional entrepreneurs across Europe - from fast-growing companies with EUR 10m+ in revenue to global family enterprises generating more than EUR 1.0bn in revenues.
Our team of approx. 80 professionals brings extensive top-tier investment experience, including previous positions at leading private equity firms, strategy consultancies and investment banks such as KKR, Auctus, Blackstone, Advent, McKinsey, BCG, Bain & Company, Goldman Sachs, and J.P. Morgan.