Descrição da Função
The Company You Will Work For
A leading organization committed to leveraging data and AI to drive innovation and operational excellence. With a strong focus on scalable infrastructure and cutting-edge technologies, the company fosters a collaborative and forward-thinking environment where engineers play a key role in shaping the future of data-driven solutions.
Your New Role
As a Data & ML Platform Engineer, you will be instrumental in designing, building, and maintaining the infrastructure that supports data processing pipelines and machine learning workflows. You will work at the intersection of data engineering, MLOps, and platform development, ensuring the robustness, scalability, and efficiency of the Data & AI Platform.
Your responsibilities will include:
Designing and implementing scalable data and ML infrastructure using cloud and on-prem technologies.
Developing and maintaining efficient data pipelines for large-scale data processing.
Managing and optimizing databases and data warehouses.
Integrating data from diverse sources to create unified datasets.
Building self-service tools for stakeholders to access insights from data and ML models.
Supporting the expansion of the Data & AI Platform.
Ensuring data security, privacy, and compliance.
Implementing data validation and quality assurance processes.
Collaborating with data scientists, analysts, and other stakeholders.
Monitoring and optimizing performance, reliability, and cost-effectiveness.
Maintaining comprehensive documentation of platform components and workflows.
What You Need to Succeed
Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
Experience: 3+ years in data & ML platform engineering or a similar role.
Skills:
Strong analytical and problem-solving abilities.
Excellent communication skills for collaboration across teams.
High attention to detail and commitment to data quality.
Adaptability to dynamic environments and multitasking.
Proficiency in Python, Go, Java, or Rust.
Experience with Docker, Kubernetes, and cloud platforms (especially Google Cloud; certification preferred).
Knowledge of SQL and NoSQL databases, data modeling, and schema design.
Familiarity with big data technologies (e.g., Spark), data warehousing (e.g., Snowflake, Redshift), and orchestration tools (e.g., Airflow).
Experience with MLOps pipelines for model training, deployment, and monitoring.
Implementation of observability stacks (e.g., Prometheus, Grafana, ELK).
Experience with Infrastructure as Code (e.g., Terraform, Ansible).
Understanding of DevOps best practices including Git, CI/CD, telemetry, and monitoring.
What the Company Can Offer You
Opportunity to work on impactful data and AI initiatives.
Collaborative and innovative work environment.
Access to modern technologies and tools.
Professional development and certification support.
Competitive compensation and benefits package.
Next Step
If you are interested in this opportunity, please send us your updated CV. If you are looking for a different type of role, feel free to reach out to explore other opportunities.
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