Job Description

🚀 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!