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
Deliver customised end‑to‑end data platform and analytics solutions on customer projects, focusing on Databricks‑based implementations across the full project lifecycle.
Compensation
We offer you for this position according to the collective agreement for employees in data processing and information technology a gross monthly salary of at least € 3215 (Consultant) or € 4286 (Senior Consultant) depending on your previous experience.
Responsibilities
Deliver customised end‑to‑end data platform and analytics solutions on customer projects
Work closely with customers to understand technical and business challenges
Design, build and optimise data pipelines, lakehouse architectures, data models and engineering workflows on Databricks
Implement and deploy robust solutions for data ingestion, transformation, orchestration, governance and analytics in production environments
Collaborate directly with customer stakeholders
Requirements
Completed studies in computer science, mathematics, physics, engineering or a comparable field
Design, build and evaluate experimental hardware and software systems as a hands‑on research architect at Bose.
Compensation
The hiring range for this position in the primary work location of Framingham, Massachusetts is: $168,300-$231,450. The hiring range for other Bose work locations may vary.
Responsibilities
Design, implement and compare software and system architectures through working prototypes and repeatable experiments.
Translate research questions into experiment specifications, baseline comparisons, measurable evaluation criteria and failure tests.
Write and debug critical software components, working directly with devices, sensors and compute platforms.
Define and test APIs, data models, messaging approaches and interfaces across hardware, models and software services.
Collaborate with Research teams to integrate ML models and signal‑processing capabilities into working systems.
Requirements
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, Robotics or a related technical discipline.
Master’s degree or higher in a related engineering or computer science discipline (preferred).
Nice to have: Master’s degree or higher
Nice to have: Experience deploying or optimizing inference on resource‑constrained hardware
Nice to have: Experience with MQTT, ROS 2, Bluetooth/BLE, device discovery or comparable communication frameworks
Lead the engineering and evolution of Optus’ cross-domain operational data capability, providing the trusted data foundation for Operational Intelligence, Automation and AI-driven Network Operations.
Compensation
Competitive remuneration and employee discounts.
Responsibilities
Own and evolve the cross-domain operational data engineering strategy and capability roadmap across Network Operations
Define the target operational data capability, information model and maturity pathway to support Operational Intelligence, Automation and AI
Lead the engineering and lifecycle management of trusted operational data products across network, OSS, BSS and cloud domains
Establish reusable patterns for real-time and batch ingestion, transformation, enrichment and delivery of operational data
Lead integration of operational data with enterprise and operational data platforms, including streaming, data lake and network data capabilities
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