Staff Data Engineer at Jobgether

, , Canada -

Full Time

Start Date

Immediate

Expiry Date

16 Aug, 26

Salary

0.0

Posted On

18 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Apache Spark, Hadoop, Flink, Kafka, Python, SQL, Docker, Kubernetes, AWS, Airflow, dbt, CI/CD, ETL/ELT Pipelines, Distributed Systems, Data Governance, Data Architecture

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Data Engineer in Canada. This is an exciting opportunity for a highly skilled data engineering professional to help shape and scale a modern global data ecosystem powering a fast-growing technology platform. In this role, you will design and optimize large-scale distributed systems capable of processing billions of transactions while enabling data-driven decision-making across the organization. You will work in a collaborative, remote-first environment alongside engineers, analysts, and data specialists who are passionate about innovation and scalable infrastructure. The position combines deep technical ownership with strategic influence, giving you the opportunity to architect robust pipelines, improve platform reliability, and explore emerging technologies. If you thrive in solving complex data challenges, mentoring others, and building systems that drive real business impact, this role offers an exceptional opportunity for long-term growth and influence. \n Accountabilities: Design, build, and maintain scalable distributed data processing systems using modern big data technologies. Develop robust ETL/ELT pipelines and real-time streaming architectures to support large-scale analytics and operational needs. Architect and optimize data lakes, data warehouses, and streaming platforms for performance, scalability, and reliability. Implement secure and fault-tolerant data infrastructure across cloud-based environments. Improve data quality, governance, lineage, and platform reliability to ensure trusted and accessible data across teams. Collaborate cross-functionally with engineers, analysts, and data scientists to deliver impactful data solutions aligned with business objectives. Drive infrastructure modernization initiatives, evaluate emerging technologies, and contribute to continuous platform improvement. Mentor junior engineers, promote best practices, and contribute to a culture of collaboration and technical excellence. Optimize system and pipeline performance through efficient partitioning, indexing, caching, and query optimization strategies. Support CI/CD workflows, automation, and deployment processes to ensure efficient and reliable delivery cycles. Requirements: Strong experience designing and managing distributed data systems and large-scale data architectures. Advanced knowledge of technologies such as Apache Spark, Hadoop, Flink, Kafka, and cloud-based data platforms. Proven expertise in building scalable ETL/ELT pipelines and streaming data solutions. Strong programming skills in Python and SQL; additional experience with Java or Scala is considered a plus. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Solid understanding of data governance, security, reliability, and infrastructure best practices. Familiarity with cloud ecosystems and tools such as AWS, Confluent, Airflow, dbt, GitHub Actions, and CI/CD workflows. Excellent analytical and problem-solving skills with the ability to independently manage projects from concept to production. Strong communication and collaboration abilities within remote and globally distributed teams. Experience mentoring team members and contributing to technical leadership initiatives is highly valued. Hospitality industry knowledge or experience working with commercial platform ecosystems is considered an advantage. Benefits: Fully remote-first working environment with global collaboration opportunities. Competitive compensation package aligned with experience and market standards. Paid time off in accordance with local labor regulations. Monthly Wellness Fridays offering extended weekends each month. Fully paid parental leave. Home office stipend based on country of residence. Access to professional development programs, technical training, and continuous learning opportunities. Manager coaching, upskilling initiatives, and internal knowledge-sharing programs. Inclusive and diverse workplace culture focused on collaboration and innovation. Opportunities to work on large-scale AI-driven and cloud-based technologies impacting a global industry. \n 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. #LI-CL1

Responsibilities

Design and maintain scalable distributed data processing systems and robust ETL/ELT pipelines to support large-scale analytics. Collaborate cross-functionally to optimize data lakes and warehouses while mentoring junior engineers to ensure technical excellence.