Data Operations Engineer

at  Trulioo

ARE YOU READY TO EMBARK ON A CAREER THAT TRULY AFFECTS PEOPLE AROUND THE WORLD? TRULIOO INVITES YOU TO BE A CATALYST FOR CHANGE IN THE DYNAMIC REALM OF DIGITAL IDENTITY VERIFICATION. AS THE GLOBAL FRONT-RUNNER IN OUR INDUSTRY, WE ARE REDEFINING HOW BUSINESSES GROW, INNOVATE AND COMPLY ONLINE.

Picture yourself at the forefront of innovation, contributing to our award-winning platform that enables organizations worldwide to quickly onboard customers, optimize costs and combat fraud. Fueled by Silicon Valley support, Trulioo stands as the trusted platform that can verify more than 5 billion people and 700 million business entities spanning 195 countries.
But Trulioo is more than a tech company. We are a united force of dedicated experts committed to establishing trust online.
Headquartered in Vancouver and with strategic hubs in San Diego and Dublin, we foster a culture of collaboration and open communication. Our offices support a hybrid model and staff typically work three days per week at a hub location. Join us where excitement meets innovation and contribute to a world where trust and technology unite.

POSITION SUMMARY:

We are looking for a detail-oriented and innovative Data Operations Engineer to join our team. Reporting to the Manager, Data Science, you will be responsible for ensuring the smooth, reliable, and efficient operation of our data analytics infrastructure to support our growing internal analytics and reporting ecosystems. You will manage data pipelines, optimize data workflows, monitor data quality, and collaborate closely with data engineering, analytics, and IT teams to support data-driven initiatives. The ideal candidate is passionate about data, enjoys solving complex problems, and thrives in a fast-paced environment.

PREFERRED SKILLS:

• Experience in ETL/ELT tools such as Talend, Fivetran, Stitch, or Matillion.
• Familiarity with data visualization tools like Tableau, Power BI, or Looker.
• Familiarity with Docker.
• Certifications in cloud technologies (AWS Certified Data Analytics, GCP Data Engineer, etc.).

• Data Pipeline Management: Design, build, and maintain data pipelines to ensure reliable data ingestion, transformation, and storage from various sources.
• Monitoring & Troubleshooting: Continuously monitor data workflows and infrastructure to identify and resolve performance bottlenecks, data quality issues, and downtime.
• Data Quality Assurance: Implement and manage processes for validating, auditing, and maintaining high data quality across all systems.
• Automation & Optimization: Develop automated solutions to streamline data operations, including monitoring alerts, reporting, and data processing workflows.
• Collaboration: Work closely with data engineers, data analysts, and IT to ensure data infrastructure meets business needs and scale as data demands grow.
• Data Security & Compliance: Ensure data pipelines and storage systems comply with data privacy regulations and industry standards for security.
• Documentation & Best Practices: Document data operation processes, workflows, and infrastructure, and advocate for best practices in data management and engineering.
• Capacity Planning & Scaling: Assist in evaluating and scaling infrastructure to accommodate the growing volume of data and users, ensuring efficient resource allocation.