Top Benefits
About the role
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.
Accountabilities
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.
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?
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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Top Benefits
About the role
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.
Accountabilities
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.
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?
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.