{"id":1048703,"url":"https://alion.io/job/loopio-data-engineer","title":"Data Engineer","company":{"id":45149,"name":"Loopio","domain":"loopio.com","url":"https://alion.io/company/loopio","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Toronto, Canada","Vancouver, Canada"],"countries":["CA"],"hiring_countries":["IN","CA","US"],"hiring_countries_total":3,"salary":{"min":103500,"max":140000,"currency":"CAD","period":"year","gross":null,"usd_annual":99524},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Aurora","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon Neptune","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Neo4j","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"Scala","optional":false},{"name":"Sisense","optional":false},{"name":"Slack","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Zoom","optional":false}],"status":"live","first_seen_at":"2026-09-18T21:38:57Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-11-03T09:55:51Z","board_verified":true,"closed_at":null,"days_open":45,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":45},"description":"Take your career to new heights with Loopio!\nLoopio’s Data Engineering Team works together on a mission to transform the RFP response process into a rapid and seamless experience. Our team works across all platform portfolio features and delivers innovative solutions where it matters the most for our customers.\nWe are looking for an experienced Data Engineer to build and support the delivery of data pipelines, used for analytics both internally by Loopio’s teams, embedded within the Loopio platform for our customers. Our perfect candidate has deep technical skills and is comfortable working in an evolving technology infrastructure. This is a unique opportunity to join a growing team of creative and passionate individuals committed to solving real world problems. You will empower engineers, product, and data scientists with tools that enable and streamline data-driven decision making, analysis, and feature development.\nYou will partner closely with ML Engineers, Architects and Data Scientists, Product Managers, and other business stakeholders to help us take Loopio’s data value to the next level.\nNote: This is an existing vacancy on the team\nWhat You’ll Be Doing\nBe responsible for building, evolving and scaling data platforms and ETL pipelines, with an eye towards growth of our business and reliability of our data\n\nPromote data-driven decision making across the organization through data expertise\n\nBuild advanced automation tooling for data orchestration, evaluation, testing, monitoring, administration, and data operations\n\nIntegrate various data sources into our Datalake, including clickstream, relational, and unstructured data\n\nDeveloping and maintaining a feature store for use in analytics & modeling\n\nPartner with data scientists to create predictive models to help drive insights and decisions, both in Loopio’s product and internal teams (RevOps, Marketing, CX)\n\nWork closely with stakeholders within and across teams to understand the data needs of the business and produce processes that enable a better product and support data-driven decision-making\n\nBuild scalable data pipelines using Databricks, and AWS (Redshift, S3, RDS), and other cloud technologies\n\nBuild and support Loopio’s data warehouse (Redshift) and data lake (Databricks deltalake)\n\nOrchestrate pipelines using workflow frameworks / tooling\n\nWhat You’ll Bring to the Team\nStrong understanding of database concepts, modeling, SQL, query optimization\n\nAbility to learn fast and translate data into actionable business results\n\nExperience in either Python (preferrably), or other common programming language (Scala, Java) for data manipulation purposes\n\nHands-on experience with the AWS services (RDS, S3, Redshift, Glue, Quicksight, Athena, ECS)\n\nStrong understanding of relational databases (RDS/Aurora) and NoSQL engines (Redis/DynamoDB/Neptune/etc).\n\nExperience with ETL & Data warehousing, building Inmon/Kimball/Data Vault models\n\nExperience with MPP frameworks such as Spark / Flink\n\nExperience with CI/CD tools (Jenkins) and pipeline orchestration tools (Databricks Jobs, Airflow)\n\nExperience working with data visualization and BI platforms (Quicksight, Tableau, Sisense, etc)\n\nExperience working with Clickstream data (Amplitude, Pendo, etc)\n\nExperience in a high growth agile software development environment\n\nExperience building and supporting large-scale systems in a production environment\n\nStrong communication, collaboration, and analytical skills\n\nDemonstrated ability to work with a high degree of ambiguity, and leadership within a team (mentorship, ownership, innovation)\n\n3+ years experience in a data engineering or a similar role\n\nAbility to clearly communicate technical roadmap, challenges, and mitigation\n\nBonus Qualifications\nExperience with container orchestration (leveraging tools like Docker, ECS, Kubernetes)\n\nExperience working with BI PaaS / SaaS solutions\n\nExperience with Natural Language Processing techniques\n\nExperience in AI-augmented SDLC\n\nExperience with graph-like data and corresponding data engines (Neo4J, Neptune, GraphFrames)\n\nWhere You’ll Work\nLoopio is a remote-first workplace because we recognize the advantages of working flexibly. We are HQ’d in Canada, with established hub regions around the world from which we hire.\n\nOur employees (or Loopers, as we call ourselves!) live and work in Canada (British Columbia and Ontario), London, and India (specifically in Gujarat, Maharashtra, and Bengaluru).\n\nThe majority of our team is based in ON and BC, which means these employees live and work remotely within a 300km radius of Toronto (within Ontario) and Vancouver (Within BC).\n\nWe offer flexible co-working locations available to Loopers in ON and BC. Those based in ON have the option of working out of our convenient co-working space located in the heart of Downtown Toronto and a 12-minute walk from Union Station. BC Loopers have the option to work centrally in Vancouver. It is whatever works best for you!\n\nYou’ll collaborate with your teams virtually across the UK, India, and North America (we’re just a Zoom call and Slack message away!) with core sync hours and focus time for headsdown work during the workday\n\nWe encourage asynchronous collaboration to effectively work as a global #OneTeam!\n\nWhy You’ll Working at Loopio\nYour manager supports your development by providing ongoing feedback and regular 1-on-1s, we leverage Lattice for our 1:1s and performance conversations\n\nYou will have the opportunity to elevate your craft and the opportunity to explore your creativity, with a dedicated professional mastery allowance for more learning support! We encourage experimentation and innovative thinking to drive business impact.\n\nWe offer a wide range of health and wellness benefits to support your physical and mental well-being, starting day 1⃣ with Loopio.\n\nWe’ll set you up to work remotely with a MacBook laptop , a monthly phone and internet subsidy, and a work-from-home budget to help get your home office all set up.\n\nYou’ll be joining a supportive culture that has thoughtfully built out opportunities for connections in a remote first environment.\n\nParticipate in townhalls, AMA (Ask-Me-Anything), and company celebrations to celebrate the big wins and milestones as #oneteam!\n\nOur four Employee Resource Groups offer opportunities for employees to learn and connect year-round.\n\nYou’ll be a part of an award-winning workplace with an opportunity to make a big impact on the business.\n\nQuestioning your qualifications? Read this ‼ Hi there, we recognize that all too often, potential candidates don’t apply for a position simply because they don’t hit every single criteria included in the job description-particularly members of underrepresented groups.\nWhether or not your experience checks off all the boxes on a job posting, we still encourage you to apply to ensure that your application receives a review from our team. We understand that a resume can only showcase so much during the applicant stage, so we've created prompts in the application for you to share more about yourself. If you've made a career transition (or a few!), you’re self taught in a new role, or you have skills/experience you’d like to highlight, we want to hear more about what you could bring to the table.\nAI in Recruitment At Loopio, we leverage artificial intelligence (AI) technology to enhance our recruitment process. These tools assist with tasks such as resume screening, drafting preliminary job descriptions, generating initial interview questions, transcription and occasionally sourcing prospective candidates. However, AI is never used to make final hiring decisions; our use of AI serves to support repetitive and administrative tasks in order to streamline our hiring and recruitment workflows. We are committed to the responsible use of AI in our hiring practices, prioritizing both an improved candidate experience and operational efficiency. Our standardized hiring practices remain focused on reducing biases, with all key hiring decisions solely made by our team. We continuously review and refine our hiring practices to align with industry best practices and evolving legal guidelines\nAI Usage in Interviews The Loopio interview process is designed to help us better understand your professional experiences, as well as your unique perspective and approach to delivery and collaboration. To ensure a fair and accurate assessment, we expect candidates to refrain from using AI-generated content to produce responses to our interview questions during the live interview, as our goal is to evaluate your own knowledge and problem-solving abilities - not those of an AI assistant. If AI-generated responses are identified during the interview, Loopio reserves the right to disqualify candidates from the interview process.\nFor specific roles that include a take-home assignment, our AI Interviewee Policy allows the use of AI for initial support; however, the final submission must be a true reflection of your personal insights, skills and decision-making.\nLoopio is an equal opportunity employer that is deeply committed to building equitable workplaces that are diverse and inclusive. We actively encourage candidates from all backgrounds and lifestyles to consider us as a future employer. 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