Data Analytics Engineer 4

Experteer Overview In this role you will design and build scalable data platforms and pipelines to support data-driven decisions for Power Delivery. You will work with cross-functional teams to deliver governed, reusable data assets and integrate operational systems with cloud lakehouse platforms. You’ll develop and maintain Databricks-based pipelines and data products, while enabling low-code and pro-code app development. This position offers an opportunity to shape data architecture and governance at scale with modern tooling and collaboration. Compensation / Benefits * Design, build, and support enterprise data pipelines using ETL/ELT * Develop scalable ingestion for structured, semi-structured, and streaming data * Build and maintain Databricks notebooks, workflows, and data pipelines * Ingest data from sources (Azure Data Factory, Kafka, APIs, files, databases) * Implement data quality checks, monitoring, and exception handling * Support Bronze/Silver/Gold data architectures in the Databricks Lakehouse * Design and maintain Delta Lake tables and data products * Develop solutions with Databricks PySpark, Spark SQL, Python, SQL * Optimize performance, scalability, and cost of the lakehouse * Support data sharing, governance, and Unity Catalog * Build and enhance business apps via Power Platform, OutSystems; develop Databricks integrations * Automate workflows and processes with users * Follow governance/security standards; implement CI/CD with GitHub and Azure DevOps * Maintain documentation, lineage, and metadata; participate in architecture reviews Tasks * Bachelor of Computer Science / Information Systems / Data Analytics / Engineering or related technical field * 3-7 years of experience in data engineering, analytics engineering, or software development * Experience building enterprise data pipelines and integrations * Experience with cloud-based data platforms Key requirements *

of Databricks Lakehouse * Design and maintain Delta Lake tables and data products * Develop solutions with Databricks PySpark, Spark SQL, Python, SQL * Optimize performance, scalability, and cost of the lakehouse * Support data sharing, governance, and Unity Catalog * Build and enhance business apps via Power Platform, OutSystems; develop Databricks integrations * Automate workflows and processes with users * Follow governance/security standards; implement CI/CD with GitHub and Azure DevOps * Maintain documentation, lineage, and metadata; participate in architecture reviews Tasks * Bachelor of Computer Science / Information Systems / Data Analytics / Engineering or related technical field * 3-7 years of experience in data engineering, analytics engineering, or software development * Experience building enterprise data pipelines and integrations * Experience with cloud-based data platforms Key requirements *