Data Platform Engineer

Key Responsibilities** - **Database Reliability & Scaling:** - Own the health and performance of their core databases. - Own and optimize their **MongoDB** clusters and **OpenSearch** indexes, which houses billions of documents. You will design sharding strategies and indexing patterns to ensure search performance. - Design and implement a multi-tier storage strategy. You will determine which data remains "hot" in production databases for their Product team and which data is offloaded to "cold/analytical" storage for AI and R&D. - **Data Access Layer:** - Build and maintain internal APIs that allow internal teams to build features without worrying about the underlying database complexities. - **Schema Evolution & Migrations:** - Lead the strategy for updating data structures across billions of records. You will design "no-downtime" migration paths for their production MongoDB and OpenSearch environments. - **Data Platform & Architecture** - Own and evolve their Core Data Architecture, ensuring it supports analytics, product features, AI workflows, and internal consumption. - Evaluate the feasibility and ROI of introducing a **Data Lakehouse architecture for long-term storage and AI training.** - Define standards for how data is ingested, stored, versioned, and exposed to downstream systems. - **Data Quality & Documentation:** - Ensure data accuracy, freshness, and consistency through validation and testing. - Maintain clear, up-to-date documentation of pipelines, schemas, and data assets to enable internal adoption. - **Collaboration:** - Act as a bridge between Core, Product, and R&D, ensuring research initiatives (e.g. data enrichment) are integrated into the Core platform. - Translate business and product needs into scalable, maintainable data solutions. - Comfortable working in async-first environments, keeping task statuses and documentation up to date for full team visibility. **What They’re Looking For** - 5+ years of experience in Backend, Data Engineering and/or Data Platform roles, specifically within **high-concurrency/high-volume** environments. - **NoSQL & Search Expert.** Professional experience tuning **MongoDB** and **OpenSearch/Elasticsearch** at massive scale (sharding, cluster topology, query optimization). - **Strong Python Skills.** Proficiency in writing production-grade, highly efficient Python. Experience with asynchronous programming (FastAPI, etc.) for building high-performance Internal APIs is essential. - **System Design & Architecture.** A strong grasp of distributed systems, including eventual consistency, message queues (Kafka/RabbitMQ), and caching strategies to protect production databases. - **Strategic Storage Thinking.** Familiarity with **Data Lakehouse** concepts (e.g., Parquet, Delta Lake, Iceberg). Proven experience building one. - Excellent communication skills and attention to documentation. - Self-managed and comfortable working cross-functionally. - Fluent in English. - Tax residency in Portugal. ## Nice to have * * * **Bonus Points** - Experience with Azure Cloud services or equivalent. - Experience with orchestration tools like **Airflow,** **Prefect**, or similar. - Exposure to AI/ML workflows or supporting AI teams with data pipelines. - Knowledge of Data Observability tools to monitor data quality and indexing lag at scale. - Interest or experience in influencer marketing or social media analytics. ## Perks * * * - Competitive salary and other social benefits - Opportunities for growth and professional development - Workplace: Remote, with the possibility of using their Nomad Offices (their next location is in Greece) - Schedule: Flexible, with the requirement to ensure a minimum of 4 hours of overlap with the normal working hours in Portugal (9 am-6 pm) - A curious, collaborative, and forward-thinking team. - They are equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees.