Automat-it is an all-in AWS Premier Partner and Managed Services Provider specializing in the startup ecosystem. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to empower fast-paced startups to grow, deliver & win. Our customers save significant time-to-market and optimize their cloud performance and costs.
We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.
We’re looking for a Senior Data & Analytics Architect to join our team and work directly with startup CTOs, engineering teams, and account teams. This is a hands-on, customer-facing architecture role where you will design and deliver production-grade data platforms on AWS.
The role is focused on turning real business problems into working systems, from early discovery and architecture design to supporting implementation. This is not a pure strategy or management role, it’s about making clear technical decisions and ensuring they hold up in production.
Work location: hybrid from Madrid
Curious about what it's really like to work at Automat-it?
Explore our benefits, culture, and what success in your first year could look like here.
If you are interested in this opportunity, please submit your CV in English.
Requirements:
- 3+ years of hands-on experience with AWS, including solution design, migration, and production systems
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2+ years in customer-facing technical roles, for example Cloud Architect, SRE, or Customer Engineer, working directly with stakeholders
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Solid understanding of modern data architectures, including batch, streaming, and lakehouse patterns
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Practical experience with core AWS data services, such as S3, Glue, Redshift, Kinesis or MSK, EMR, Athena, Lambda, and IAM
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Familiarity with broader AWS infrastructure, including networking, IAM, and compute patterns
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Experience working with real-time or near real-time data processing
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Strong grasp of data modeling, pipelines, and storage optimization
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Ability to reason about trade-offs, not just select tools
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Ability to lead end-to-end technical engagements, from discovery through delivery
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Comfort operating in fast-moving environments with ambiguous requirements
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Clear communication skills, able to explain technical decisions to both technical and non-technical stakeholders
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Strong communication skills in English. Spanish is a plus
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Basic understanding of security and access control in AWS environments
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Experience writing HLDs, SOWs, and supporting pre-sales engagements
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Experience with ETL processes, data lakes, and pipelines
Nice to Have
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Experience with Iceberg, dbt, or similar modern data tooling
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Familiarity with Kubernetes, Docker, Terraform, and CI/CD pipelines
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AWS certifications (Solutions Architect, Data Analytics, or similar)
Automat-it is committed to fostering a workplace that promotes equal opportunities for all. We firmly believe that cultivating a diverse workforce is crucial to our success. Our recruitment decisions are grounded in your experience and skills, recognizing the value you bring to our team.
Key Responsibilities:
- Design and deliver end-to-end data platforms on AWS, covering ingestion, storage, processing, and serving layers, including Well-Architected reviews and contributions to SOWs and HLDs
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Work directly with startup customers to understand requirements, challenge assumptions, and shape practical solutions
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Lead technical discussions, workshops, architecture reviews, and POCs
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Translate ideas and early concepts into clear architectures, including HLDs, SOWs, and implementation direction
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Make and explain trade-offs across cost, performance, scalability, and complexity
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Stay close to delivery, supporting teams to ensure solutions are implemented correctly
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Collaborate with Data Engineers, DevOps, Solution Architects and Account Managers to move projects from concept to production
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Contribute to internal standards, reusable patterns, and reference architectures
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Operate in a fast-paced, project-based environment with multiple customer engagements
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Stay up to date with modern Data Engineering and Analytics practices, and contribute to internal enablement, patterns, and knowledge sharing
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Work in a customer-facing environment that includes occasional travel, both locally for meetings and events, and internationally around once per quarter
