Cloud Data Architect
🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀
Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.
We’re looking for a Cloud Data Architect to join our team and help design and evolve large-scale data platforms for a major banking project currently undergoing a data modernization process. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀
In this role, you will join a Data Architecture team responsible for defining standards, patterns, and best practices that guide multiple data engineering teams building modern data products on AWS.
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🚀 What We Do
Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
Amazon Web Services
Astronomer
Databricks
🌟 Our Values
📊 We are Data Nerds
🤗 We are Open Team Players
🚀 We Take Ownership
🌟 We Have a Positive Mindset
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀
Responsibilities 🤓
Participate in defining the reference data architecture, including ingestion, transformation, storage, and consumption patterns on AWS.
Collaborate in establishing standards for data modeling, naming conventions, lineage, data quality, and technical documentation.
Design and implement dbt models and Airflow pipelines supporting analytical workloads on Redshift.
Design and implement data testing and quality strategies using dbt tests and tools such as Elementary Data.
Actively participate in architecture discussions, design reviews, and technical decision-making across the data ecosystem.
Collaborate with engineering teams to ensure consistent adoption of architecture standards and best practices.
Work closely with business and technology stakeholders to align technical decisions in complex organizational environments.
Required Skills 💻
Experience working on production data platforms at scale.
Experience working in banking, financial services, or large enterprises with comparable organizational complexity.
Strong ability to design architectures and propose solutions to complex data problems, not just execute implementations.
Hands-on experience with: dbt, Airflow, Amazon Redshift, Amazon S3 and SQL.
Experience implementing data testing and observability practices (dbt test, Elementary Data, Great Expectations or similar).
Strong communication skills and the ability to collaborate with multiple stakeholders and technical teams.
🎁 Perks
AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
In-Company English Lessons.
Birthday off + an extra vacation week (Mutt Week! 🏖️)
Referral bonuses – help us grow the team & get rewarded!
Maslow: Monthly credits to spend in our benefits marketplace.
✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
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Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.
We’re looking for a Cloud Data Architect to join our team and help design and evolve large-scale data platforms for a major banking project currently undergoing a data modernization process. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀
In this role, you will join a Data Architecture team responsible for defining standards, patterns, and best practices that guide multiple data engineering teams building modern data products on AWS.
\n
🚀 What We Do
Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
Amazon Web Services
Astronomer
Databricks
🌟 Our Values
📊 We are Data Nerds
🤗 We are Open Team Players
🚀 We Take Ownership
🌟 We Have a Positive Mindset
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀
Responsibilities 🤓
Participate in defining the reference data architecture, including ingestion, transformation, storage, and consumption patterns on AWS.
Collaborate in establishing standards for data modeling, naming conventions, lineage, data quality, and technical documentation.
Design and implement dbt models and Airflow pipelines supporting analytical workloads on Redshift.
Design and implement data testing and quality strategies using dbt tests and tools such as Elementary Data.
Actively participate in architecture discussions, design reviews, and technical decision-making across the data ecosystem.
Collaborate with engineering teams to ensure consistent adoption of architecture standards and best practices.
Work closely with business and technology stakeholders to align technical decisions in complex organizational environments.
Required Skills 💻
Experience working on production data platforms at scale.
Experience working in banking, financial services, or large enterprises with comparable organizational complexity.
Strong ability to design architectures and propose solutions to complex data problems, not just execute implementations.
Hands-on experience with: dbt, Airflow, Amazon Redshift, Amazon S3 and SQL.
Experience implementing data testing and observability practices (dbt test, Elementary Data, Great Expectations or similar).
Strong communication skills and the ability to collaborate with multiple stakeholders and technical teams.
🎁 Perks
AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
In-Company English Lessons.
Birthday off + an extra vacation week (Mutt Week! 🏖️)
Referral bonuses – help us grow the team & get rewarded!
Maslow: Monthly credits to spend in our benefits marketplace.
✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
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