Senior Data Engineer

Sago Mini is an award-winning publisher of preschool apps and toys worldwide. We are supported by a team of artists, designers, developers, product managers, thinkers, and doers devoted to play. With over 100 million downloads and three subscription services featuring 45+ apps, Sago Mini brings thoughtful design to life for kids and parents worldwide. Along with Toca Boca and Originator, we’re part of the Piknik family – a collection of top-rated apps for kids in one subscription.

About the Role

As a member of the Data & Analytics team, you will have a strong background in data engineering and foundational experience in Machine Learning workflows on GCP. You will be responsible for designing, developing, automating and maintaining data pipelines, as well as supporting the deployment and monitoring of ML models. You will mentor Junior Data Engineers and collaborate within the Data & Insights team as well as externally with Program/Project Managers, analytics and other cross functional teams - ranging from product management, marketing to finance and our partner organizations - to ensure our data ecosystem is robust, scalable and optimized for insights. You will be instrumental in building and refining our data pipelines, ensuring data integrity, and implementing best practices for data governance.

This is a hybrid role that will require your presence in our downtown, Toronto office four days per week.

What You’ll Be Doing

Data Pipeline Development:

• Design, develop, and maintain scalable and robust data pipelines, to support various data-driven applications.

• Utilize GCP services like Dataflow, Pub/Sub, BigQuery, and Cloud Storage for data ingestion, transformation, and storage.

• Ensure data quality, integrity, and availability through automated testing and monitoring.

Data Warehousing and Governance:

• Develop and manage ETL/ELT processes to integrate data from various sources into a central data warehouse using Airflow, DBT and other tools

• Create efficient data models optimized for analytics and reporting use cases

• Implement data validation and monitoring tools to detect anomalies and ensure quality.

• Optimize data storage and retrieval processes using GCP’s BigQuery and other cloud-native data storage solutions.

Collaboration and Communication:

• Partner with Data Scientists & ML Engineers, Analysts, and Product teams to understand needs, provide actionable insights, and ensure alignment between data capabilities and business objectives.

• Document data pipelines, architectures, and processes for internal use and future reference.

• Communicate technical concepts and solutions effectively to non-technical stakeholders.

Performance Optimization:

• Continuously monitor and optimize data pipelines and storage solutions for performance and cost-efficiency.

• Identify and resolve bottlenecks in data processing and model deployment pipelines.

Machine Learning Support:

• Collaborate with data scientists to build and maintain data pipelines that feed machine learning models.
• Assist in the deployment and operationalization of machine learning models, ensuring they run efficiently in production environments.
• Utilize foundational ML knowledge to support model training, feature engineering, data preparation tasks and building models eventually.

Qualifications and Skills

• 3+ years of experience in data engineering, with a focus on development and deployment of accurate and optimized data models.
• Bachelor’s degree in computer science, information science or a resume full of relevant experience.

• Experience in cloud platforms and its offerings like Google or Azure or AWS (GCP strongly preferred).

• Technical Skills:

• Strong programming skills in Python and SQL

• Understanding and experience in object-oriented design principles.

• Experience with schema design and data modeling.

• Hands on experience in using tool like DBT, Airflow etc

• Understanding of reporting tools like Preset, Tableau or Power BI, is a plus.

• Familiarity with Git or similar tools for version control.

• Strong verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.

• Strong analytical & problem-solving skills and the ability to work independently or as part of a team.

Nice to Haves

• Experience with DevOps tools and practices (e.g. CI/CD pipelines, Docker, Kubernetes).
• Knowledge of machine learning pipelines or basic ML model deployment.

• Experience in a Mobile App industry and/or B2C Subscription business model.

About the Process

• You’ll get an email response confirming we’ve received your application, and we’ll let you know within a few weeks if we’d like to schedule a follow-up.
• If you’re moving ahead, we’ll book a call to learn more about your experience.
• If that goes well, we’ll send you a short homework assignment to get a better feel for your skillset.
• If the assignment goes well, we’ll book a couple more interviews with you and our hiring teams to dive deeper prior to making a final call.

We welcome and encourage applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process.

-

Based in Toronto, Sago Sago Toys of Spin Master Limited a leading global children’s entertainment company that creates, designs and manufactures a diversified portfolio of innovative toys, games, products and entertainment properties. We hire humble and collaborative people who care about doing great work. Sago Mini is an equal opportunity employer. We value diversity at our company.