Data Platform Developer

About the role As a Data Platform Developer, you’ll design, build, and maintain scalable, secure, and high‑performance data platforms that support analytics, data science, BI, and AI use cases for geoscience data. Working closely with other data platform and software developers, you’ll help ensure data availability, integrity, and accessibility across Seequent’s platforms and connected data and application ecosystem. In this role, you will have the opportunity to: Design, build, and maintain cloud‑based data platforms. Create and manage scalable data pipelines and infrastructure for ingesting, validating, storing, transforming, and processing data from various internal and external sources, using batch and real-time methods. Move data from various sources into data warehouses or data lakes. Develop and maintain CI/CD pipelines and observability tools to automate deployments and testing. Consume, design, develop, publish, and support internal and external web APIs to provide interface to geoscience data. Develop and optimize data models to support analytical workloads. Provide reliable, well-structured datasets and semantic layers for BI tools, dashboards, advanced analytics, and AI/ML use cases. Ensure continuous monitoring of data platform health, performance, and availability. Provide operational tier 2/3 support, in conjunction with the Cloud Ops team, for data platform issues. To be successful in this role, you should have: Bachelor’s degree in computer science, data engineering, or related field. 5+ years of experience in data architecture or data engineering roles. Experience with enterprise-scale data platforms for managing structured, semi-structured and unstructured data. Experience maintaining Data Lakes and/or Data Warehouses in production environments. Experience with relational and no-SQL data storage mechanisms. Strong proficiency in SQL, Python, JSON. Experience with cloud platforms and data services (i.e. Databricks, Snowflake). Knowledge of data modelling, ETL/ELT processes, and data warehousing concepts. Familiarity with containerization (i.e. Docker, Kubernetes), CI/CD pipelines, and infrastructure-as-code. Experience with streaming technologies (i.e. Kafka, Event Hub) and API integrations. Additional Information Office-based working environment, work from our Toronto office two or more days per week. #LI-NP1