{"id":197738,"url":"https://alion.io/job/the-vanguard-group-sr-data-engineer-specialist","title":"Sr Data Engineer, Specialist","company":{"id":253,"name":"The Vanguard Group","domain":"vanguard.com","url":"https://alion.io/company/vanguard","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":89,"ghost_share":0.079,"stale_share":0.506,"repost_share":0.202,"time_to_fill_p50_days":27,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":90000,"max":140000,"currency":"CAD","period":"year","gross":null,"usd_annual":99056},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"GitHub","optional":false},{"name":"IAM","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"dbt","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-03T17:24:35Z","employer_posted_date":"2026-09-03","last_verified_at":"2026-10-31T00:56:44Z","board_verified":true,"closed_at":null,"days_open":57,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":57},"description":"We are looking for a Sr Data Engineer with in-depth expertise in AWS, Databricks, and modern dataarchitecture and data modeling to help build the next generation of our data foundation , including data\nplatforms such as Advisor360, CRM integrations, ETF/MF data pipelines, and other enterprise analytics assets.\nThis is a senior, highly autonomous role. You will operate as a technical consultant and data architecture\nthinker, working closely with stakeholders to understand ambiguous business needs, conduct independent\ninvestigations, and design solutions that are scalable, reliable, and aligned to both business and technology\ngoals.\nIdeal candidates have 5+ years of data engineering experience and thrive in environments where they drive\nclarity, define standards, and elevate engineering best practices across the team\nResponsibilities:\nData Engineering & Architecture:\nDesign, build, and optimize scalable, secure, and repeatable data pipelines using AWS (S3, Glue, Lambda, Step Functions, Redshift, IAM) and Databricks (PySpark,Lakeflow,Delta Lake, Unity Catalog).\n\nServe as the technical leader for data ingestion pipelines, modeling new datasets such as Advisor360, CRM, ETF, and Mutual Fund platforms.\n\nApply strong data modeling (dimensional, canonical, and domain-driven) principles to support analytics, reporting, and AI/ML use cases.\n\nEnsure alignment with enterprise data architecture standards, promoting reusability, governance, and long-term maintainability.\n\nConsultative Problem Solving:\nWith limited guidance, independently perform deep investigations, identify data issues, and propose solutions that balance performance, cost, risk, and business needs.\n\nEngage business stakeholders to gather ambiguous requirements, ask the right questions, and translate them into clear technical designs.\n\nProvide thought leadership and recommend technical patterns, frameworks, and toolsets.\n\nData Quality, Reliability & Operations:\nImplement robustdata quality frameworks, monitoring, and alerting to ensure high trust in business-critical data assets.\n\nTroubleshoot data inconsistencies and ensure proper logging, testing, and recovery mechanisms across pipelines.\n\nLead regression testing, software upgrades, and production deployments with strong change control discipline.\n\nCollaboration & Leadership:\nLead all phases of solution development-from design to deployment and operationalization.\n\nMentor and guide other engineers in coding standards, architecture patterns, Databricks best practices, and AWS platform usage.\n\nPartner with Data Architecture, Analytics, Product, and Business teams to deliver solutions that improve decision-making.\n\nProvide training sessions and documentation to uplift the data engineering maturity across the organization.\n\nSpecial Projects:\nParticipate in strategic initiatives such as AI readiness, data unification efforts, metadata strategy, and enterprise integration roadmaps.\n\nDrive continuous improvement in engineering frameworks, onboarding workflows, and platform capability.\n\nRequired Skills:\n5+ years of experience in data engineering, data architecture, or large-scale distributed data systems.\n\nExpert-level experience with cloud platforms such as AWS, GCP, or Azure, leveraging services for data storage, ingestion, pipeline orchestration, database or lakehouse management,data transformation.\n\n5+ years of hands-on experience designing, developing, and supporting enterprise-scale data pipelines on the Databricks Lakehouse platform usingPySpark, Delta Lake, Databricks Workflows, andLakeflowDeclarative Pipelines\n\nStrong background in data modeling (dimensional, canonical, data vault, or domain-driven).\n\nProven ability to work independently with minimal direction and deliver high-quality solutions in ambiguous environments.\n\nDemonstrated experience translating complex business problems into scalable technical solutions.\n\nStrong SQL and Python skills, with emphasis on ETL/ELT pipeline development.\n\nExperience with CI/CD, GitHub, DevOps workflows, and automated testing.\n\nPreferred Skills:\nExperience in asset management, wealth management, or financial services (ETF, Mutual Funds, CRM, Advisor analytics).\n\nExperience with enterprise data quality tools and metadata management concepts.\n\nFamiliarity with modern semantic layers,dbt, or domain-oriented data mesh concepts.\n\nUndergraduate degree or equivalent professional experience in Computer Science, Engineering, Information Systems, or related field.\n\nPay Transparency\nExpected Salary Range: $90,000-$140,000\nOur compensation ranges are based on role, level, and local market. Individual pay within the range is determined by factors such as job-related skills, experience, and relevant education or training. For part-time roles, pay will be pro-rated based on regularly scheduled hours.\nIn addition to the range above, Vanguard’s total compensation package may include performance-based incentives, discretionary bonuses, and other perks. We also offer comprehensive benefits such as health insurance, accident and life insurance, and retirement savings plans. Your recruiter will be able to provide additional details on the total compensation offering during the hiring process.\nAI Disclosure Statement\nVanguard does not use artificial intelligence (AI) or automated decision-making tools in its recruitment process. All application reviews and hiring decisions are made by our recruitment team.\nAccommodations\nVanguard is committed to fostering an accessible and inclusive workplace. We are committed to providing barrier-free and accessible employment practices in compliance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code. If you require accommodation at any stage of the recruitment process, please inform us. We will work with you to meet your needs, and you can reach us at  , quoting the job ID and job title.\nHow We Work\nVanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. 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