Senior Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in Canada.

This role offers the opportunity to design and scale modern data platforms that support high-volume financial technology solutions.
You will build reliable data infrastructure capable of processing hundreds of millions of events while enabling smarter business decisions.
Working within a fully distributed engineering environment, you will collaborate with product, operations, and business teams to solve complex data challenges.
You will contribute to the evolution of cloud-native data architectures, open-source technologies, and scalable data processing systems.
This position is ideal for an experienced data engineer passionate about distributed systems, automation, and building impactful platforms.
You will play a key role in creating efficient data solutions that support innovation, growth, and global expansion.

• Design, develop, and maintain scalable data platform architectures capable of supporting high-volume, low-latency data processing.
• Build and optimize forward and reverse ETL patterns to deliver reliable data flows to internal teams, business stakeholders, and external systems.
• Develop scalable transformation layers that enable consistent integrations with business intelligence and analytics tools across different functions.
• Expand and maintain modern data lakehouse architectures, including ingestion, transformation, storage, monitoring, and consumption layers.
• Collaborate closely with product, sales, marketing, operations, and engineering teams to understand data requirements and deliver effective solutions.
• Manage production data systems, troubleshoot issues, and ensure reliable performance of critical data infrastructure.
• Implement best practices around data quality, observability, automation, and system scalability.
• Contribute to technical decisions involving distributed systems, cloud infrastructure, and open-source data technologies.

Requirements:

• 7+ years of professional experience in data engineering, including experience building scalable data platforms handling more than 100 million events per day.
• Strong programming experience in at least one language, with advanced knowledge of Python and SQL.
• Proven experience designing and operating cloud-native data solutions using platforms such as Google Cloud Platform and related data services.
• Hands-on experience with technologies including Docker, Kubernetes, Helm, and modern cloud infrastructure practices.
• Strong knowledge of relational databases, object storage systems, and data lakehouse technologies such as Apache Iceberg.
• Experience building transformation layers using SQL-based modeling frameworks such as dbt.
• Practical experience with ETL orchestration tools and frameworks such as Apache Airflow and Airbyte.
• Experience working with streaming data systems such as Kafka.
• Familiarity with DevOps practices, Infrastructure as Code (IaC), and tools such as Terraform.
• Deep understanding of distributed systems, storage architectures, transactions, and query processing using technologies such as Trino.
• Ability to work effectively in a fast-paced, remote environment while adapting solutions to evolving business needs.
• Strong analytical skills, problem-solving abilities, and a collaborative mindset.

Benefits:

• Competitive salary package with stock options.
• Comprehensive health benefits.
• Fully remote work environment across North America and LATAM regions.
• One-time home office setup allowance of $500 USD for new hires.
• Monthly remote work stipend of $150 USD through a company expense card.
• Opportunity to work with a globally distributed team of experienced engineers and technology professionals.
• Exposure to large-scale data systems, modern cloud technologies, and open-source solutions.
• Supportive environment focused on innovation, ownership, and continuous learning.