This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist based in Canada. We are seeking a highly skilled Data Scientist to design and build scalable data solutions that enable advanced analytics, machine learning capabilities, and data-driven decision-making. This role sits at the intersection of data engineering, science, and business, requiring strong technical expertise and the ability to transform complex data challenges into impactful solutions. You will contribute to building robust data pipelines, optimizing large-scale data platforms, and enabling intelligent products through analytics and machine learning. The position offers the opportunity to collaborate with engineering, product, security, and business teams in a fast-paced technology environment. You will help shape data architecture, governance practices, and scalable solutions that support innovation and operational excellence. This opportunity is ideal for a data-driven problem solver who enjoys ownership, technical challenges, and creating measurable business impact. ### Accountabilities: As a Data Scientist, you will be responsible for designing, developing, and optimizing data solutions that support analytics, machine learning, and business intelligence initiatives. You will work across technical and business teams to build reliable data platforms, improve data accessibility, and establish best practices for scalable data operations. - Design, build, and optimize scalable data pipelines and ETL/ELT workflows using modern cloud data technologies. - Develop advanced data models supporting user analytics, customer insights, predictive modeling, and recommendation systems. - Integrate data from multiple sources, including databases, streaming platforms, cloud storage, APIs, and operational systems. - Implement automated testing, CI/CD processes, and data quality frameworks to ensure reliable and maintainable pipelines. - Collaborate with Data Science, Machine Learning, Backend Engineering, Security, and Infrastructure teams to productionize data-driven solutions. - Mentor junior engineers and contribute to improving data modeling, performance optimization, and engineering practices. - Optimize algorithms, queries, and warehouse performance through advanced tuning techniques. - Build monitoring solutions and dashboards to track pipeline health, data latency, and operational performance. - Establish data governance standards, including metadata management, lineage, documentation, and schema versioning. - Contribute to the evolution of scalable data architectures and modern data platform strategies. - Translate business requirements into technical solutions while communicating complex concepts clearly to stakeholders. ## Requirements: The ideal candidate combines strong data science expertise with hands-on experience building scalable data systems, optimizing algorithms, and collaborating across technical teams. - 5+ years of experience working as a Data Scientist or in a related data-focused engineering role. - 3+ years of experience with Spark frameworks and large-scale data processing. - Strong proficiency in SQL and Python with proven experience developing scalable ETL/ELT solutions. - Experience designing and managing data pipelines using tools such as Airflow, Prefect, dbt, or similar technologies. - Strong understanding of data modeling approaches, including Kimball, Data Vault, or hybrid methodologies. - Experience with cloud platforms such as GCP or AWS and technologies supporting batch and real-time data ingestion. - Familiarity with Kafka, API-based integrations, and distributed system architectures. - Strong knowledge of algorithm performance optimization, query tuning, and warehouse orchestration. - Experience working with Snowflake, including Snowpark, Streams, Tasks, Snowpipe, and performance optimization. - Ability to develop scalable data solutions while maintaining reliability, quality, and security standards. - Experience deploying machine learning features, managing ML pipelines, or supporting recommendation systems is a plus. - Background in gaming, e-commerce, advertising technology, or similar data-intensive industries is an advantage. - Experience mentoring engineers or leading technical initiatives is preferred. - Strong ownership mindset with the ability to work independently in a fast-paced environment. - Excellent communication skills with the ability to bridge technical and business discussions. - Collaborative approach with strong problem-solving and analytical capabilities. ## Benefits: - Competitive salary range of $150,000–$220,000 per year, depending on experience and qualifications. - Comprehensive medical, dental, and vision insurance coverage. - Paid time off and employee wellness benefits. - Personalized career development roadmap and professional growth opportunities. - Access to training, learning resources, and skill development programs. - Supportive and collaborative work environment focused on innovation and creativity. - Opportunity to work on impactful data solutions using modern technologies. - Culture that values collaboration, ownership, and continuous improvement. - Commitment to supporting employees’ physical, mental, and emotional well-being. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! [Why Apply Through Jobgether?](https://jobgether.com/how-jobgether-works) Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1