Data Architect (with German)

Core Tech Stack:

AWS, Amazon EMR, S3, Glue, Athena, Redshift, Lake Formation, Kinesis, Hadoop, Apache Spark, Apache Airflow, ETL/ELT, Data Lakes, Data Governance, Data Modeling, CI/CD, Agile/Scrum, Jira, Confluence
Required Qualifications:

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5+ years of experience as a Data Architect / Data Platform Architect

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Strong experience designing enterprise-scale data platforms and data architectures

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Strong knowledge of AWS data services and cloud architecture

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Extensive experience with AWS Data Lake and Amazon EMR

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Strong background in Hadoop and Apache Spark

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Experience with Apache Airflow and workflow orchestration

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Strong understanding of ETL/ELT patterns and modern data pipelines

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Experience designing batch and/or streaming data architectures

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Extensive experience in Data Migration, Data Integration and system integration

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Strong knowledge of Data Governance, Data Quality, Metadata Management and Data Lineage

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Strong understanding of Data Security, IAM, encryption and access-control concepts

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Experience with data modelling and designing data flows across distributed systems

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Understanding of relational, NoSQL and analytical data storage concepts

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Experience designing solutions for scalability, high availability, performance and resilience

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Experience with CI/CD and infrastructure/data pipeline automation

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Ability to define architecture principles, standards, patterns and technical documentation

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Experience working in Agile/Scrum environments

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Practical experience with Jira, Confluence and Microsoft Teams

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Strong stakeholder-management and communication skills

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Ability to work effectively with both technical teams and business stakeholders

- AWS Data Analytics certification

- ITIL Foundation certification

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At least four relevant project references within the last 8 years for each major capability area

- Very good command of English

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German language skills (ideally C1/C2 or native level) will be a strong advantage. Candidates without German are also welcome to apply if they have a strong technical fit.

Nice to Have:

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Experienced in using AI tools in day-to-day workflow

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Experience with additional AWS data services such as S3, Glue, Athena, Redshift, Lake Formation or Kinesis.

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Knowledge of modern Lakehouse architectures.

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Experience with event-driven and real-time data architectures.

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Familiarity with Data Mesh and Data Fabric concepts.

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Experience working in large-scale international or regulated enterprise environments.

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Knowledge of enterprise architecture frameworks and architecture governance processes.

Project Description:

We are looking for an experienced Data Architect / Data Platform Architect to join a complex enterprise environment and take responsibility for designing scalable, secure, and well-governed data platforms.

The role combines hands-on data architecture expertise, AWS cloud technologies, data governance, migration and integration, as well as close collaboration with both technical and business stakeholders. We are seeking someone who can operate beyond individual data pipelines or engineering tasks, taking ownership of architectural decisions, challenging requirements, defining target-state solutions, and guiding engineering teams through implementation.

The ideal candidate combines strong technical expertise with an enterprise architecture mindset and is confident communicating complex architectural decisions to both technical and non-technical audiences.

Please note: This is a full-time freelance project engagement with an initial contract duration of 1 year.
Scope of Services:
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Design and evolve enterprise data architecture and cloud-based data platforms.

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Define architecture for Data Lakes, data processing and analytics solutions on AWS.

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Design scalable data ingestion, transformation, integration and processing pipelines.

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Define architectural standards, patterns and best practices for data platforms.

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Design and oversee data migration and system integration strategies.

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Ensure appropriate Data Governance, Data Quality, Data Security and access-control standards.

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Define data models, data flows, interfaces and integration patterns across complex environments.

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Support architectural decisions regarding batch and real-time data processing.

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Work with engineering teams on Hadoop, Spark, Airflow and AWS-based solutions.

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Drive automation and support CI/CD practices for data platforms and pipelines.

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Ensure solutions meet requirements related to scalability, performance, reliability, security and maintainability.

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Collaborate with Data Engineers, Cloud Architects, Security teams, Product Owners and business stakeholders.

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Translate business and technical requirements into target architecture and implementation roadmaps.

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Conduct architecture reviews and provide technical guidance to delivery teams.

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Create and maintain architecture documentation, data flows, standards and technical specifications.

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Support Agile/Scrum delivery and participate in technical workshops with stakeholders.

Originally posted on Himalayas