Note: The job is a remote job and is open to candidates in USA. Primetag is a fast-growing SaaS company in the influencer marketing analytics space, providing a proprietary platform and large-scale database to help brands and agencies optimize influencer marketing operations. The Data Platform Engineer will own and evolve the company’s core data infrastructure, including databases, search systems, storage architecture, APIs, migrations, and data quality. The role also partners with Product, Backend, AI/R&D, and Analytics teams to build scalable production systems and support data and AI initiatives.

Responsibilities

• Own the health and performance of our core databases
• Own and optimize our 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 our Product team and which data is offloaded to "cold/analytical" storage for AI and R&D
• Build and maintain internal APIs that allow internal teams to build features without worrying about the underlying database complexities
• Lead the strategy for updating data structures across billions of records. You will design "no-downtime" migration paths for our production MongoDB and OpenSearch environments
• Own and evolve our 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
• 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
• 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

Skills

• 5+ years of experience in Backend, Data Engineering and/or Data Platform roles, specifically within high-concurrency/high-volume environments
• Professional experience tuning MongoDB and OpenSearch/Elasticsearch at massive scale (sharding, cluster topology, query optimization)
• Proficiency in writing production-grade, highly efficient Python. Experience with asynchronous programming (FastAPI, etc.) for building high-performance Internal APIs is essential
• A strong grasp of distributed systems, including eventual consistency, message queues (Kafka/RabbitMQ), and caching strategies to protect production databases
• 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 is a must for this position.
• 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

Benefits

• Opportunities for growth and professional development
• Remote workplace, with the possibility of using Nomad Offices (our next location is in Greece)
• Flexible schedule, 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.

Company Overview