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SSENSE: Senior Data Engineer


This is a Full-time position in Val-Des-Arbres, QC posted July 20, 2021.

Company DescriptionSSENSE, pronounced [es-uhns], is a Montreal-based fashion platform with global reach.

Founded in 2003, SSENSE is pacing the vanguard of directional retail with a mix of luxury, streetwear, and avant-garde labels.

We produce industry-leading original content and take pride in building our own technology solutions and systems from scratch.

Our field of focus has grown beyond that of a typical e-commerce entity as we explore the nexus of content, commerce, and culture.Currently serving 150 countries, generating an average of 88 million monthly page views, and achieving high double digit annual growth since inception, SSENSE is becoming a cultural protagonist in its own right.Job DescriptionSSENSE is looking for a Senior Data Engineer to join our rapidly growing technology team.

The Senior Data Engineer will take complex product roadmap features, break them down into their required technical components, and develop them independently.

They own at least one component of the SSENSE technical stack and hold accountability for its SLAs.

The ideal candidate will actively contribute to knowledge dissemination within the organization, participate in the recruiting and onboarding of new employees, and mentor Junior Developers on the team.ResponsibilitiesProduct deliveryBuild, test and operate stable, scalable data pipelines that cleanse, structure and integrate disparate data sets into a readable and accessible format for end-user facing reports, data sciences and ad-hoc analysesDevelop a deep understanding of the product roadmap for the squad, including future features to be developedContribute to high-level estimation and participate in laying out the development sequences, challenging the product roadmap and identifying areas where technical debt can be reduced or avoidedComplete independently complex development tasks and actively contribute to pushing code to productionWrite testable, efficient, and reusable code suitable for continuous integration and deployment, respecting best practices and SSENSE development standardsReview Unified Modeling Language (UML) diagrams and technical documentationOwnership and accountabilityBe accountable for code quality by conducting adequate testingBe accountable for performance, reliability, scalability and resilience of at least one technical component owned by the squad through SLAs and monitoringSolve complex technical problems and mentor/support other technical staff on data modelling and ETL related issuesContribute to cross-squad initiatives, acting as a change agent amongst peers to foster adoption of new processes or technical solutionsKnowledge sharing and coachingReview Pull Requests to guide and upskill other Data Engineers on various technical topicsActively contribute to SSENSE University (the internal peer learning platform) to promote continuous learningParticipate in the onboarding of new Data EngineersArchitectureContribute to solution designs, challenging other members on technical decisions and explaining the technical design to junior developers so they can write documentation for the rest of the teamRecruitingParticipate in HR recruiting events, helping to identify and recruit top developersQualificationsBachelor’s degree in Computer Science, Engineering, or a related technical field, Master’s degree an assetA minimum of 5 years of Functional Programming and/or Object Oriented Programming (OOP) experienceA minimum of 3 years experience writing and optimizing SQL queriesA minimum of 3 years experience with Apache Spark for big data processingExtensive knowledge of Python programming language and its data manipulation libraries (Pandas and Numpy)Expertise in data modeling and an advanced understanding of data architectureExpertise with RDBMS and NoSQL databases at scaleExperience with Apache Airflow or other similar data pipelining and workflow scheduling framework (Luigi, Azkaban)Ability to use containers, orchestration frameworks, and other DevOps tools (Kubernetes, Terraform, Giant Swarm, etc.)Proficiency with cloud resources (AWS/Google Cloud/Azure) with the ability to operate them for the components owned.

Certification is an asset.Knowledge of the AWS services (Redshift, Glue, Athena, S3, etc.) an assetKnowledge of big data technology (Databricks, Hadoop, Hive, Pig, Presto) an assetFamiliarity with continuous integration and automated pipeline tools (Jenkins, Travis, etc.)Proficiency in GitSkillsHighly analytical and detail-orientedAbility to coach and mentor junior employees to achieve personal and professional goalsTeam player with a high sense of accountability and ownershipAbility to influence and drive changeSolution-oriented mindset and can-do attitude to overcome challengesAbility to thrive in a fast-paced environment and master frequently changing technologies and techniquesAdditional InformationWORLD CLASS TECHNOLOGY Technology is at the core of everything we do at SSENSE.

Driven by an engineering mindset and a problem-solving attitude, we blend fashion with technology to deliver an unparalleled experience to our customers as we build seamless, custom solutions to deliver the SSENSE offering.WORLD CLASS TEAMThe SSENSE tech team is responsible for an international headless commerce platform.

Working in an agile environment, our squads are made up of experienced innovators in Product Management, QA, Design, DevOps, Software Development, Machine Learning, Data Engineering, and Security.

Headquartered in Montreal, our technology organization has been growing at a rate of 2X year-over-year and is doubling once again in 2021 as we expand across Canada, US, and Europe.WORLD CLASS PLATFORM The SSENSE platform runs on Amazon Web Services making use of serverless microservices across web, mobile and app.

Our event-source architecture already achieves over 10,000 requests / second and growing at an unmatched pace, currently unseen across the industry.

Our data-driven culture of innovation empowers every product team across the tech organization to explore building, testing and learning with the latest in Machine Learning techniques.

Our automated continuous improvement DevOps model (making use of both blue / green and canary deployments) results in an average of 50 production releases every day.Read more about us on our SSENSE Tech Blog.