Data Engineer

• Design and maintain robust, scalable data pipelines using Kubeflow, Python, and Snowflake, ensuring optimal performance and reliability.
• Follow best practice standards for deployment and the use of CI/CD tools.
• Govern end-to-end data architecture with a focus on data quality, security, compliance, and lifecycle management.
• Expertise in Requirements engineering and refinement
• Build efficient and scalable data models ensuring optimal query performance and responsiveness.
• Ensure seamless data flow across ingestion layers, data models, and visualization outputs.

Analytics & Visualization

• Conduct in depth data analysis to identify trends, variances, and improvement opportunities, transforming insights into clear and actionable recommendations for business stakeholders.
• Translate complex datasets into actionable insights through Power BI dashboards.
• Apply DAX and Power Query techniques to create dynamic, user friendly, and high performance visualizations for operational and analytical use cases.
• Collaborate with business stakeholders, strategy, and IT stakeholders to define KPIs, reporting standards, and analytical models that support strategic decision-making.
• Perform ad-hoc analysis and maintenance tasks.

Collaboration & Documentation

• Maintain version control, documentation, and workflow traceability in GitHub to ensure transparency, reproducibility, and collaboration across teams.
  • Work closely with business stakeholders to gather requirements, validate outputs, and iteratively refine solutions.