Data Platform Engineer

About the job We are HCLTech, one of the fastest-growing large tech companies in the world and home to 225,000+ people across 60 countries, supercharging progress through industry-leading capabilities centered around Digital, Engineering and Cloud. The driving force behind that work, our people, are diverse, creative, and passionate, raising the bar for excellence on a regular basis. We, in turn, work hard to bring out the best in them as we strive to help them find their spark and become the best version of themselves that they can be. If all this sounds like an environment, you’ll thrive in, then you’re in the right place. Join us on our journey in advancing the technological world through innovation and creativity. About the Role: Join our client's team as a Senior+ Data Engineer supporting their innovative geoscience data platform. This small, dynamic team acts as the critical bridge between geoscience disciplines, enterprise technology, and external partners, enabling the digital transformation of geoscience data management and analytics. You will be instrumental in building, operationalizing, and evolving the geoscience data backbone, transforming diverse datasets—including drillhole, geochemistry, imagery, geophysics, remote sensing, and operational data—into trusted, governed data products using Databricks, Azure Data Factory, enterprise GIS, and Power BI platforms. Key Responsibilities: Develop and optimize data pipelines in Databricks and Azure Data Factory for large-scale data migration, system integration, and AI workflows Design and implement data models, ensuring high performance, scalability, and data quality Collaborate with geoscience teams, enterprise technologists, and external partners to deliver robust data solutions Support the deployment and maintenance of AI-enabled geoscience workflows within our client’s cloud environment Ensure best practices in software engineering, CI/CD automation, and documentation for maintainability and scalability Ideal Candidate Profile: We are seeking a highly skilled, senior-level Data Engineer with extensive experience in cloud data platforms, data pipelines, and software engineering practices. Must-Have Skills & Experience: Databricks: Advanced PySpark, Spark SQL, Delta Lake, Unity Catalog, workload automation Azure Data Factory: Pipeline creation, orchestration, parameterization, performance tuning SQL & Data Modelling: Strong analytical SQL, window functions, performance optimization Python: Production-quality code, modular design, testing, reusable libraries Software Engineering: Version control (Git), pull requests, code reviews, structured development CI/CD: Azure DevOps pipelines, environment promotion automation Data Pipeline Testing: Validation, unit/integration testing, data quality assurance Documentation & Maintainability: Clear, well-structured code with comprehensive documentation Strongly Preferred Skills: AI-assisted development tools such as GitHub Copilot or similar AI-capable Databricks features (e.g., Genie, Mosaic AI, dashboards) DataOps practices, Infrastructure-as-Code (Terraform, Bicep, DABs) Prompt engineering for AI workflows Containerization (Docker) and basic Kubernetes knowledge Power BI reporting, Azure gateway configuration Nice-to-Have Skills: Basic geoscience domain knowledge (drillhole, geochemistry data) Workflow orchestration tools such as Argo Workflows Data governance, metadata management, lineage tracking Why Join Us? This is an excellent opportunity to contribute to a cutting-edge geoscience data platform within a global leader in mining. You'll work in a collaborative environment, utilizing the latest cloud and AI technologies, and have the chance to influence data-driven decision-making at a strategic level.