{"id":3653772,"url":"https://alion.io/job/the-vanguard-group-senior-lead-data-ai-engineer","title":"Senior Lead Data & AI Engineer","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":76,"open_postings":75,"ghost_share":0.12,"stale_share":0.56,"repost_share":0.2,"time_to_fill_p50_days":28,"computed_at":"2026-11-05T05:54:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","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":null,"salary_estimate":null,"experience_years_min":9,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-02T00:00:00Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-05T18:40:44Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Position Overview\nJoin us in a high-impact, high-visibility role where you will lead the design and delivery of enterprise-scale Data & AI solutions that power analytics, operational decision-making, and AI innovation across the organization.\nWe are seeking an experienced Senior Lead Data & AI Engineer with 9-12+ years of experience in Data Engineering and modern cloud-based data platforms, with deep expertise in Databricks, Lakehouse architecture, and AWS. This role will be responsible for building scalable data foundations, reusable engineering frameworks, and AI-ready data products that accelerate business value and enable advanced analytics and Generative AI use cases.\nThe ideal candidate combines strong hands-on data engineering expertise with solution architecture, technical leadership, and a passion for modernizing data ecosystems through automation, metadata-driven engineering, and cloud-native technologies.\nKey Responsibilities\nData Engineering Leadership\nLead the architecture, design, and delivery of enterprise-scale data engineering solutions leveraging Databricks and AWS.\nDesign and implement scalable, resilient, and reusable data pipelines supporting batch, streaming, and event-driven workloads.\nDrive engineering best practices across data ingestion, transformation, orchestration, testing, monitoring, and deployment.\nEstablish reusable frameworks, patterns, and standards to accelerate delivery and improve engineering quality across teams.\nDatabricks & Lakehouse Engineering\nArchitect and implement modern Lakehouse solutions utilizing Databricks, Delta Lake, Unity Catalog, and cloud-native services.\nDevelop metadata-driven and configuration-based frameworks that standardize ingestion, transformation, quality validation, and deployment processes.\nDesign and implement Delta Live Tables (DLT), Lakeflow Pipelines, and Databricks Workflows to automate enterprise data processing.\nBuild trusted, governed, and reusable data products that support analytics, reporting, data science, and AI initiatives.\nOptimize platform performance, scalability, reliability, and cost efficiency across large-scale workloads.\nData Platform Modernization\nLead migration and modernization initiatives from legacy platforms to cloud-native data architectures.\nImplement data observability, monitoring, lineage, metadata management, and quality controls throughout the data lifecycle.\nPartner with architecture and platform teams to advance enterprise data platform capabilities and engineering standards.\nSupport implementation of CI/CD, Infrastructure-as-Code, automated testing, and DevSecOps practices.\nAI & Advanced Analytics Enablement\nBuild AI-ready data foundations that support machine learning, Generative AI, and intelligent business applications.\nPartner with Data Scientists, AI Engineers, and business teams to operationalize data products and AI solutions.\nSupport implementation of vector search, semantic models, retrieval-augmented generation (RAG), and knowledge-driven AI capabilities.\nContribute to AI orchestration and agent-based solutions where business value can be accelerated through intelligent automation.\nEnable reliable integration between AI applications and enterprise data platforms.\nGovernance, Security & Data Quality\nImplement enterprise-grade governance using Unity Catalog, metadata repositories, and data quality frameworks.\nEnsure compliance with enterprise security, privacy, and regulatory requirements.\nDesign automated controls for data validation, observability, lineage, and operational monitoring.\nPartner with governance organizations to improve trust and accessibility of critical data assets.\nStakeholder & Team Leadership\nAct as a trusted technical advisor to business, analytics, and technology stakeholders.\nMentor and provide technical leadership to Data Engineers and platform teams.\nLead architecture reviews, design workshops, and engineering governance activities.\nTranslate complex technical concepts into actionable business outcomes for leadership audiences.\nQualifications\nBachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related discipline.\n9-12+ years of experience in Data Engineering, Data Platform Engineering, or Analytics Engineering.\n5+ years of hands-on experience building enterprise solutions on Databricks.\nStrong expertise in Lakehouse architecture, Delta Lake, Unity Catalog, and modern data engineering patterns.\nProven experience building large-scale data pipelines using Spark, PySpark, SQL, and Python.\nDeep experience with AWS services supporting Data & AI platforms.\nExperience implementing Delta Live Tables, Lakeflow, Databricks Workflows, and metadata-driven engineering approaches.\nStrong understanding of data modeling, data products, data governance, metadata management, and data quality frameworks.\nExperience with CI/CD, Infrastructure-as-Code, automated testing, and cloud-native engineering practices.\nDemonstrated leadership experience mentoring engineers and leading complex technical initiatives.\nStrong communication and stakeholder management skills.\nPay Transparency\nExpected Salary Range: 93,000 to 165,000\nRole status: existing vacancy\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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