Design and build robust batch and real‑time data pipelines on GCP
Own data quality within delivery area, defining and implementing data contracts, quality checks, and observability instrumentation
Develop and maintain in‑house connectors and third‑party native integrations for IG’s ingestion estate
Contribute to engineering standards and best practices across the squad, including code review, dbt modelling patterns, CI/CD pipeline hygiene, and change control for shared datasets
Support feature engineering and model data pipelines for Data Science, helping lay foundations for AI‑ready data
Lead the design and evolution of large-scale, mission-critical data systems powering a tax automation platform, owning the end-to-end flow from ingestion and validation to domain modeling, file generation, and regulatory submissions.
Locations (3)
Argentina
Brazil
Montevideo, Montevideo, Uruguay
Compensation
Annual Salary Range: $2,021,800.00 - $2,695,700.00
Pay Basis: Monthly
The expected base salary range for this role varies by location and is expressed in local currency. The posted range reflects the anticipated hiring range for successful candidates at the time of hire, based on relevant job‑related skills, experience, geographic location, and business needs. Base pay offered to new hires may vary within the posted range depending on individual qualifications and market considerations.
In addition to base pay, this role may be eligible for other elements of Vertex’s total compensation package, which may include participation in the Vertex Bonus Plan (VOB), a role‑specific sales commission or bonus, and/or equity grants, where applicable.
Responsibilities
Lead design and evolution of large-scale data systems
Lead product management for Gogolook’s Anti‑Scam Common Services, defining roadmap, APIs, and developer experience for internal and external customers.
Responsibilities
Define and manage the Anti‑Scam Common Services roadmap spanning data ingestion, reputation services, shared reporting, and AI‑ready interfaces.
Translate business needs into measurable product priorities and balance reusable shared‑service investments against one‑off requests.
Treat internal product managers, business developers, and engineers as first customers and improve self‑service adoption.
Lead product development for source registration, data import, metadata, ingestion contracts and monitoring.
Own product priorities for shared risk services covering phone numbers, URLs, content, and report handling.
Requirements
Bachelor's degree or equivalent in Computer Science, Engineering, or related field
Nice to have: Experience building or managing internal developer platforms
Nice to have: Experience with shared services used by multiple teams
Nice to have: Experience with anti‑scam, trust and safety, cybersecurity, fraud prevention, identity, risk intelligence, or reputation services
Nice to have: Experience with enterprise customers, government agencies, or telecom operators
We are looking for a Traceability Integration Engineer (Product Integration Engineer) that builds and maintains the integration flows that connect the product ecosystem: SAP, SaaS solutions, LCNC apps, data products, events, devices and microservices.
Responsibilities
Collaboration with PO, Product TTL, & Product Solution Engineers
Investigate multi-system issues
Provide integration RCA and recommendations
Support new features requiring new integrations
Collaborate with business analysts and other functional experts to thoroughly understand and document detailed business requirements for product traceability, including data points & verification needs and translate them into clear integration specifications.
Requirements
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical/supply chain field.
Nice to have: Digital Product Passeport (DPP) solutions like EON
Nice to have: integration technology certifications
Transformer la donnée et l'intelligence artificielle en leviers d'action concrets pour optimiser nos chaînes logistiques, automatiser nos processus et sublimer notre offre produit.
Responsibilities
Concevoir, packager et faire vivre la donnée comme un produit fini, fiable, documenté et exposé via des Data Contracts clairs
Concevoir des solutions prédictives et génératives qui automatisent les tâches répétitives des métiers
Intégrer les outils d’IA dans les pratiques de delivery et accompagner la montée en maturité des équipes métiers
Définir la vision du produit, gérer le backlog, mesurer la valeur métier et prioriser les cas d’usage
Formaliser les besoins fonctionnels en utilisant des outils d’IA pour accélérer la rédaction des user stories
The TD Global Technology & Services team is seeking a Senior Business Systems Analyst with expertise in Generative AI process automation products to help shape AI-enabled solutions enabling complex enterprise workflows.
Compensation
$81,600 - $115,200 CAD
Responsibilities
Analyze complex business and technology workflows, identifying decision points, dependencies, constraints, manual activities, control requirements, and opportunities for AI integration.
Develop current-state and future-state models that clarify how proposed AI automations affect processes, people, technology, data, controls, and operational responsibilities.
Collaborate with key stakeholders to determine solutions, assess impact to existing work processes and systems, and how to manage the integration.
Lead technology requirements management for high risk, strategic initiatives.
Model end-to-end agentic workflows, business rules, behavioral logic, approvals, exceptions, escalations, and human intervention points.
Requirements
Bachelor’s degree in Business, Technology, Engineering, Information Systems, or a related field
Lead privacy-centric engineering initiatives within JPMorgan Chase’s Chief Data & Analytics Office, managing the Data Privacy & Governance roadmap and driving technical direction for privacy impact assessments and technology integrations.
Responsibilities
Manage the Data Privacy & Governance roadmap
Lead firmwide privacy initiatives
Drive technical direction for Privacy Impact Assessment
Structure roadmap delivery and operating model
Oversee engineering projects, risks, issues, and dependencies
Requirements
Nice to have: Complex data governance
Nice to have: Security and compliance requirements
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