Quantexa
Senior Data Engineer (Secret II Clearance)
Ottawa · Senior
Sponsorship not specifiedDetected 15 days ago
PythonJavaScalaBashGitElasticsearchGCPAzureDockerJenkinsDevOpsSparkData AnalysisData EngineeringRecruitingCommunicationMentoring
About the role
- Our technology started out in FinTech, helping tackle serious criminal activity.
- Now, its potential is virtually limitless.
- Working at Quantexa isn't just intellectually stimulating.
Responsibilities
- Our recruitment process is designed to be inclusive and accessible.
Requirements
- You'll have a background in hands-on technical development, with at least three years of industry experience in a data engineering role or equivalent, and preferably at least four years of software industry experience.
- Proficiency in Scala, java, python, or a programming language associated with data engineering.
- Experience with a variety of modern development tooling (e.g. Git, Gradle, Nexus) and technologies supporting automation and DevOps (e.g. Jenkins, Docker and a little bit of good old Bash scripting).
- Knowledge of testing libraries of common programming languages (such as ScalaTest or equivalent).
Compensation
- Regularly bench-marked salary rates
Benefits
- Competitive salary & Company bonus
- Competitive annual leave, plus your birthday off, parental leave, PTO, and observed holidays
- Comprehensive benefits coverage, including mental health support, fitness reimbursements, and financial well-being
- Tax-advantageous benefits, such as commuter benefits, healthcare, and dependent care
Company info
- What we are is a collection of bright, passionate minds harnessing complexities and helping our clients and their communities.
- We are committed to fostering an inclusive and diverse work environment, continuously improving to ensure everyone belongs.
Equal opportunity
- Equal Opportunity Employer.
Apply directly at Quantexa →Create a free account for alerts like thisView Quantexa immigration profile
This listing is sourced directly from Quantexa's careers page and normalized into a canonical job model.