Data/Analytics Engineer

Requirements

• Master’s degree in Computer Science, Engineering, Statistics, or a related field.
• 3+ years of experience in data engineering, analytics engineering, or a related role.
• Proficiency in Python and SQL.
• Experience with dbt.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Clickhouse).
• Strong analytical and problem-solving skills, with attention to detail.
• Ability to communicate complex data concepts to both technical and non-technical stakeholders.

Nice to Have

• Experience with machine learning pipelines, MLOps, and feature engineering.
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code (e.g., Terraform).
• Background in building self-service data platforms for analytics and AI use cases.

What you will be doing

• Design, build, and maintain scalable data pipelines, ETL processes, and analytics infrastructure. Automate data quality checks and validation processes.
• Collaborate with cross-functional teams to understand data needs and deliver high-quality, actionable solutions.
• Optimize data storage, retrieval, processing, and queries for performance, scalability, and cost-efficiency.
• Define and enforce data governance, metadata management, and data lineage standards.
• Ensure data integrity, security, and compliance with industry standards.

Perks and Benefits

• Dynamic and collaborative team passionate about AI and its potential to transform society.
• Diverse workforce thriving in competitive environments and driving innovation.
• Creative, low-ego, and team-spirited culture.
• Distributed teams in France, USA, UK, Germany, and Singapore.
• Pioneering company shaping the future of AI with a meaningful impact.