Data Engineering

- Design, develop, and maintain scalable data pipelines to ingest, transform, and store large volumes of data both on-premises (SSIS etc.) and in the cloud (Azure, AWS, GCP)
- Ensure data integrity, accuracy, and availability for analytical and operational use.
- Collaborate with software engineers, data scientists, and business stakeholders to understand data requirements and implement solutions.
- Optimize and improve existing data workflows and ETL processes.
- Implement data governance and security best practices.
- Manage data storage solutions, such as data lakes and data warehouses.
- A successful history of manipulating, processing and extracting value from large, disconnected datasets.
- Deploy data solutions in the cloud and with database tools (SQL, NoSQL).

Data Analytics

- Perform exploratory data analysis to identify trends, patterns, and insights.




- Develop and maintain reports, dashboards, and visualizations using BI tools (e.g., Power BI, SaaS VA).
- Conduct statistical analysis and modeling to support business strategies.
- Communicate findings and recommendations to stakeholders in a transparent and concise manner.
- Use SQL and other query languages to extract and manipulate data from various sources.
- Create plans and strategies to integrate data models and improve service delivery.
- Develop and share service metrics and performance dashboards.
- Facilitate the frequent delivery of services and deliverables to ensure the successful creation of the target state while mentoring Agile Teams to grow their analytics fluency.

📌 GOAPR445 Data Analyst (Canada)
🏢 Omega solutions
📍 Canada