Cloud Data Architect - DBT

5 мес. назад

ArgentinaLATAMRemote

awsdbtbig datamachine learning

Design and evolve large-scale data platforms using Big Data and Machine Learning technologies for a banking data modernization project.

🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀   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.

Define and maintain data architecture guidelines: Ingestion, transformation, storage, consumption, and governance patterns.
Provide strong, independent judgment in design reviews and architecture decisions across the client's data ecosystem.
Deliberately manage technical debt and uphold high standards for data testing, observability, and CI/CD pipelines.
Act as the trusted technical liaison: Translate business needs into technical solutions, and technical decisions into executive-level language.
Identify opportunities to evolve the scope of our services and shape them into technical-commercial proposals.

Proven track record as a Senior Data Engineer or Data Architect, with hands-on experience leading technical teams in production environments.
Expert command of dbt, Airflow (MWAA), Redshift, S3, and advanced SQL.
Experience working within highly complex enterprise or corporate organizations.
Ability to design architectures and propose solutions from scratch, rather than just executing pre-defined plans.
Strong communication and negotiation skills across all organizational levels—from engineers to the board of directors.

DataOps and CI/CD applied to data: GitHub Actions, Terraform, Docker.
Lakehouse architectures.
Legacy-to-cloud migrations.
Data Mesh and distributed data ownership.
Governance and cataloging tools: OpenMetadata, DataHub, Atlan, or similar.
AI Agents applied to data: LangGraph, LangChain, LiteLLM, RAG.
AI-assisted development integrated into real workflows (not just concept demos).
Cloud certifications (AWS Data Engineer, Solutions Architect, or equivalent).

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.
Amazon Web Services
Astronomer
Databricks
📊 We are Data Nerds
🤗 We are Open Team Players
🚀 We Take Ownership
🌟 We Have a Positive Mindset