#14 Senior DataOps Engineer

About the role

🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀

At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.

We are looking for a Senior DataOps Engineer to join our team and work on a long-term project with a leading financial institution in Argentina.🐶🚀 Your mission will be to industrialize Databricks as the corporate data platform, with a standardized, automated, observable, and reliable model to develop and operate data products, reducing manual tasks and individual dependencies and enabling self-service so the platform can scale without increasing the operational load on the team.

🚀 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 🤓 - Design and implement CI/CD for Databricks, including controlled promotion across environments.

- Manage Infrastructure as Code for workspaces, permissions, compute, service principals, and policies.

- Create reusable templates and standards for new data products and pipelines.

- Automate the onboarding of data products, users, and services.

- Implement observability: monitoring, logging, alerting, and operational metrics.

- Define SLOs/SLAs, retries, reprocessing, and recovery mechanisms.

- Optimize platform reliability, performance, and capacity.

- Apply FinOps practices: tagging, cost allocation, and cost optimization.

- Document standards, runbooks, and operational procedures.

- Collaborate with Architecture, Security, Infrastructure, Governance, and Development teams to align platform decisions.