Senior Data & AI Architect at reeeliance IM GmbH

Hamburg, Berlin, Germany -

Full Time

Start Date

Immediate

Expiry Date

28 Sep, 26

Salary

0.0

Posted On

30 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architecture, AI Architecture, Python, SQL, Databricks, Snowflake, BigQuery, LLM, RAG, Vector Databases, MLOps, dbt, Apache Spark, Airflow, CI/CD, Terraform

Industry

IT Services and IT Consulting

Description

About the role We are looking for a Senior Data & AI Architect to design, build, and manage the end-to-end data infrastructure that powers intelligent AI applications. In this role, you will act as a systems-oriented Senior Data & AI Architect for our clients. You are not just a developer writing code in isolation; you are a strategic thinker who bridges the gap between complex data networks and tangible business value—directly on-site with clients. With a strong "Builder’s Mindset," you prioritize sustainable, scalable, and secure engineering over temporary quick fixes. You will bring this mindset into high-stakes, regulated environments (such as Financial Services and Med-Tech) where data quality, compliance, and governance are core product features, not administrative burdens. Your responsibilities As a Senior Data & AI Architect, you will shape the data ecosystems of our clients and represent reeeliance’s architectural vision At this role, you will design and build the technical foundation for generative AI and machine learning workloads, including feature stores, vector databases (e.g., Pinecone, pgvector), embedding layers, and scalable ingestion pipelines Your role will be to define and implement robust modeling standards for structured, semi-structured, and unstructured data (utilizing Data Vault, dimensional modeling, and schema-on-read approaches) You will be responsible for structuring and conducting assessments to map a client's data landscape, identify readiness gaps (schema quality, lineage, governance maturity) and establish reusable assessment frameworks You will treat regulatory requirements (e.g., EU AI Act, BCBS 239, GDPR, GxP) not as a burden, but as a technical feature, automate policies and security guardrails directly into CI/CD pipelines and platform provisioning In this role, you will champion the "Golden Path" philosophy, value clean architecture, automated testing, documentation, and total reproducibility (via Git, MLflow, and containerization) as non-negotiables, hands-on engineer who is as comfortable deep-debugging a pipeline as you are designing high-level workflows As a Senior Data & AI Architect, you will act as a bilingual bridge, by explaining vector embeddings to a business executive and business ROI to a developer, listening first to understand the client's problem before proposing technical solutions You will coach client teams and mentor junior colleagues at reeeliance, enabling them to adopt modern, high-quality data engineering practices and scaling our architectural mindset Our requirements 5+ years of experience in data engineering, data architecture, or a related software engineering role Experience in or a strong interest in working within regulated sectors like Financial Services or Med-Tech, with an understanding of how regulatory standards shape data architectures Deep expertise in architecting and scaling solutions on Databricks, Snowflake, BigQuery, or similar modern cloud platforms High proficiency in Python and SQL, solid experience with transformation and orchestration tools (e.g., dbt, Apache Spark, Airflow, Prefect) Hands-on experience building architectures for Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), practical knowledge of vector databases (e.g., Pinecone, Weaviate, pgvector) and embedding management Solid understanding of MLOps patterns and tooling (e.g., MLflow, Kubeflow, SageMaker, or Vertex AI) to ensure models, code, and data versions are fully auditable and reproducible Proven ability to build systems focused on automated data quality, data lineage, metadata catalogs, and real-time process monitoring Familiarity with decentralized data architectures, such as Data Mesh, and separating platform capabilities (Data Fabric) from domain data products Comfort with CI/CD tools, containerization (Docker, Kubernetes), and IaC (Terraform) A passion for understanding how tools work under the hood and proactively exploring emerging tech trends (e.g., transition from basic RAG to Agentic Reasoning) Strong consultative skills, empathy, and the ability to explain complex technical designs in plain language and experience in mentoring team members and helping them grow What we offer Space to grow: Taking ownership in international projects while continuously expanding your skills Mentorship and Onboarding: Structured introduction supported by dedicated mentor Cutting-edge workspace: Work with the latest technology and modern equipment to drive innovative solutions Long-term stability: A permanent employment in a family-oriented and people-focused company Diverse & inclusive environment: Join a truly international environment and collaborate daily with teammates from over 15 different nationalities Balance matters or work-life harmony: A work schedule designed to promote well-being and productivity Team culture & connection: Social events and structured team-building days held in Berlin and Hamburg Language courses: Learn, improve or practice your conversational skills on language platform Lingoda Never stop learning: You’ll receive a dedicated budget to industry-leading platforms like Udemy and MasterClass to sharpen your technical expertise and leadership skills …and many other Job perks (childcare subsidy, company pension scheme, job bike, etc…) About us We love data... reeeliance guides regulated enterprises in turning AI readiness into AI-embedded operations, redesigning the workflows where risk, compliance, and business decisions actually happen. We design, build, and govern the data foundations that make it possible, combining strategic advisory, data and AI engineering, and deep SAP expertise across Hamburg, Berlin, and Porto.

Responsibilities

Design and build end-to-end data infrastructure and technical foundations for generative AI and machine learning workloads. Act as a strategic bridge between complex data networks and business value while ensuring regulatory compliance in high-stakes environments.