Data Engineer

The Data Engineer at Keypath Education will collaborate with the APAC Data Engineering team to design and maintain essential data infrastructure and pipelines. They will act as a technical expert in system integration, data warehouse modeling, and creating semantic layers for actionable insights. The role emphasizes optimizing data pipelines and models for efficiency and reliability, driving growth across the Asia & Pacific region.Key responsibilities include managing the data engineering lifecycle, analyzing business domains, understanding source data, and designing effective data pipelines and models. The candidate must have advanced skills in analytics and reporting, with the ability to build robust data models and integration pipelines for comprehensive data processing and visualization.Key Accountabilities include (but are not limited to) the following:Data Integration:Design and implement scalable and efficient data integration pipelines using Azure Data factory which ingests structured and semi-structured data from diverse sources like APIs, databases, file-shares, data streamsDevelop resilient system integration solutions leveraging Azure Functions, Python, .Net codebases and related development frameworksData Modelling:Design and develop comprehensive data warehouse models using Kimball dimensional modelling techniques that are scalable and efficientDevelop and manage Azure Analysis Services semantic-layer tabular models to support business intelligence initiatives and self-service capabilitiesMaintain data dictionaries and metadata repositories to document data models and their elements, ensuring compliance with cross-region and customer data policiesInsights & Analytics:Create comprehensive Power BI solutions including advanced data models, interactive reports, data visualisation and dashboards through expert use of Power Query, DAX, and Power BI ServiceImplement robust Power BI security, including Row-Level Security (RLS), to meet diverse cross-functional team and regional access needsManage the PowerBI instance including workspace, datasets, monitoring and troubleshooting and user access issuesAdvanced Analytics:Develop scientific modeling solutions using Machine Learning and Artificial Intelligence technologies to generate actionable insightsImplement predictive and prescriptive analytics solutions using advanced analytics methodologies to optimize decision-making and improve business outcomesDelivery:Deliver complex data engineering solutions using Agile methodologies and iterative development processesEnsure quality of data engineering solutions by aligning with team’s architecture, development, productivity standards and processesCollaborate closely with the Product team and subject matter experts to understand and translate data engineering and integration requirements into technical solutionsEnsure alignment of data engineering solutions with broader organizational strategic objectives and key performance indicatorsDevOps:Design and maintain robust Continuous Integration and Continuous Deployment (CI/CD) pipelines for seamless system integrationsDevelop and maintain automation frameworks that enhance deployment efficiency and reduce manual interventionConduct thorough code reviews and manage pull request approvals in Azure DevOps to ensure code quality and knowledge sharingOperations:Proactively monitor data product health, security, data governance adherence, and regulatory compliance, ensuring operational stability and risk reductionManage and resolve data related incidents through thorough root cause analysis and timely implementation of effective remediation activitiesOptimise the performance of data pipelines, queries, and overall data products for enhanced speed, efficiency, scalability and cost reductionReview and implement continuous improvement activities to boost data product efficiency and quality