* Architect simple and effective solutions, based on business requirements, the current and future data platform and the latest standards in data and analytics, design and plan how to deliver them;
* Provide technical knowledge and guidance to product managers, software developers, data scientists;
* Plan new technology deployments and provide technology Proof of Concepts to evaluate and validate the potential of new technologies to help leverage data, with a strong focus on creating highly reusable data assets, data quality, observability, and discoverability;
* Define KPIs and collect metrics to measure progress towards achieving our analytical vision;
* Technology observation – research new/emerging technologies that could benefit predictive analytics solutions;
* Spread innovation and best practices within and outside the team, creating a community of technology experts, organizing workshops, demonstrations and training;
* Carry out capacity planning;
* Identify dependencies in parallel execution projects in the DT&A portfolio and involve the analytical scope;
* Work closely with DT&A partners from other service lines, architects and highlight cross-functional issues or synergies.
Experiences
* Experience in at least one reference programming language (preferably Python or C#) and in architecting software solutions;
* Experience in architecture for self-service data and analytics platforms in the cloud, ideally based on the MS Azure framework;
* Experience in data modeling;
* Experience in data integration, with ETL technologies and API implementations;
* Experience in designing and implementing data lake, data warehouse and database;
Any of the following considered an advantage:
* Experience in the commodities sector, preferably agribusiness;
* Experience supporting a data science platform;
* Agile structure, product mindset;
* Data visualization tools, preferably PowerBI;
Skills
* Big data techniques: high-performance computing, spark, scalable solutions.
Required Languages
* English (Basic)
Required Education
Completed Higher Education in Computer Science, Business/Management Information Systems, Computers/Systems/Industrial Engineering, Business Analysis, Data Science, Operations Research or Statistics.
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