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Senior Data & Analytics Architect
with strong hands-on technology expertise and proven consulting experience. The candidate will lead Data & AI strategy initiative leveraging
AWS and Snowflake , while guiding the client through modern data architecture patterns including
Lakehouse ,
Open Table Formats (Delta / Iceberg) , and AI-enabled use cases. This is a client-facing role requiring strong stakeholder management, requirements gathering, and the ability to independently drive a consulting engagement end-to-end. Key Responsibilities
Consulting & Engagement Leadership Lead discovery workshops and requirement gathering sessions with business and technology stakeholders. Translate business objectives into scalable data architecture and implementation roadmaps. Drive engagement governance, solution articulation, and executive-level communication. Provide thought leadership on modern data platform architecture and AI enablement. Architecture & Design Design and implement modern
Data Warehouse and Lakehouse architectures . Define data models (dimensional, normalized, Data Vault where appropriate). Architect solutions using: (Good to have - will have Solution Architects supporting) AWS ecosystem (S3, Glue, Lambda, IAM, Redshift, etc.) Snowflake (Data Warehouse, Snowpark, Streams/Tasks, Data Sharing) Open table formats (Delta Lake / Apache Iceberg) Recommend best practices for scalability, security, governance, and cost optimization. Engineering Oversight Guide ingestion, transformation, and orchestration strategies. Ensure implementation aligns with data governance and compliance standards. AI & Emerging Technologies Identify and design AI/ML enablement patterns (data readiness for ML, feature engineering pipelines). Advise on modern data stack evolution including: Lakehouse patterns Open table formats (Delta / Iceberg) Data mesh principles (if applicable) Evaluate new technologies and recommend adoption roadmap. Required Skills & Experience Experience 8+ years of total experience in Data Engineering / Data Architecture / Analytics Consulting. Proven experience working in consulting engagements (client-facing). Experience working with US-based clients is strongly preferred. Technical Expertise Strong hands-on experience with
AWS
data services. Strong experience with
Snowflake
architecture and optimization. Deep understanding of: Data Warehousing concepts (dimensional modeling, performance tuning) Lakehouse architecture patterns Open table formats: Delta Lake and Apache Iceberg Experience with cloud-native data pipelines and modern ELT frameworks. Understanding of data governance, security, and compliance in cloud environments. Exposure to AI/ML data pipelines and AI-driven analytics use cases. Consulting & Soft Skills Strong requirement gathering and stakeholder management skills. Ability to articulate technical solutions to business leadership. Experience driving projects independently. Strong written and verbal communication skills. Ability to operate in ambiguous environments typical of PE-backed portfolio transformations. Preferred Qualifications Experience working with Private Equity firms or portfolio companies.
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Sprachkenntnisse
- English
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