Data engineering advisor developing scalable data platforms and pipelines for Desjardins. Designing, integrating, and improving data systems aligned with business needs.
About the role
- Data Engineering intern at Hyper Hippo contributing to data platform development and maintenance. Collaborating with teams to optimize data pipelines and enhance analytics capabilities.
Responsibilities
- Contribute to the development and maintenance of modern ELT data pipelines that collect, organize, process, and prepare data from a variety of sources.
- Help build and improve analytical datasets and reporting layers that support decision-making across the business.
- Partner with data engineers, analysts, and business stakeholders to understand data requirements and translate business concepts into reliable data solutions.
- Help expand and enhance data quality monitoring to ensure reliable and trustworthy data for decision-making.
- Research, evaluate, and integrate new data sources, tools, and techniques that expand our understanding of players, games, and business performance.
- Apply data engineering and business intelligence best practices to create scalable, maintainable, and well-documented solutions.
- Identify opportunities for process improvements and contribute ideas that enhance our data platform, analytics capabilities, and ways of working.
Requirements
- Currently enrolled in a post-secondary degree program in Computer Science, Data Engineering, Mathematics, or related field.
- Experience writing Python and SQL.
- Foundational understanding of data cleaning, transformation, and preparation techniques.
- Familiarity with data modeling concepts and relational database fundamentals.
- Strong analytical and problem-solving skills, with a desire to learn and apply new technologies.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
- Experience working with Git and collaborative software development practices.
- Nice to Have: Experience with big data tools (Spark/PySpark).
- Familiarity with cloud-based data platforms or data warehouses such as Databricks, Snowflake, Redshift, or BigQuery.
- Experience with cloud data services (Azure, AWS, GCP).
Benefits
- Customized orientation workshops
- E-learning resources
- Mentoring support
- Opportunity to build professional network in the creative technology industry
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