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The role leads the development and architecture of data pipelines, models, and automation across data sources.It works in agile teams and collaborates across business and technology partners to del... Voir plus
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Job Overview
Job Function
The role leads the development and architecture of data pipelines, models, and automation across data sources. It works in agile teams and collaborates across business and technology partners to deliver resilient, reliable, and governed data infrastructure.
Job Duties
Pipeline Development: Design and develop scalable ELT/ETL pipelines using cloud-native tools.
Data Modeling: Implement dimensional models and integrate data sources for BI/reporting.
Performance Optimization: Tune queries and jobs for speed and reliability.
Tooling and Automation: Build CI/CD pipelines, reusable modules, and automation scripts.
Cross-Functional Collaboration: Work with analysts, architects, and other developers to deliver cohesive data solutions.
Documentation and Metadata: Maintain documentation and contribute to enterprise metadata/catalog tools.
Agile Execution: Lead user story delivery and actively participate in sprint planning and retrospectives.
Support and Monitoring: Provide Tier 2 support and monitor pipeline health proactively.
Innovation and Improvement: Identify and implement enhancements to improve system scalability and user satisfaction.
Qualifications
Education
Role requires knowledge to design, develop, and optimize data solutions using SQL, Python, Spark, and Azure services. This knowledge is considered to be normally acquired either through the successful completion of a four-year university education in Computer Science, Software Engineering, or another related discipline.
Experience
Experience in data development with strong fluency in SQL, Python, Spark, and Azure services is required. A period of 6-8 years is considered necessary to gain this experience
CPUS Engineering employs artificial intelligence (AI) tools as part of its recruitment process to enhance efficiency and consistency. These tools may assist with activities such as application screening, candidate evaluation, and summarization of interview feedback.
AI-generated outputs are intended to supplement, not replace, human judgment. All final hiring decisions are made by qualified human decision-makers who exercise professional discretion in reviewing and assessing candidate information alongside any AI-generated insights.
CPUS Engineering ensures that the use of AI in recruitment complies with all applicable employment laws, human rights legislation, and privacy regulations. The organization is committed to maintaining fairness, transparency, and non-discrimination throughout the hiring process.
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