Senior data platform strategist
this role is responsible for envisioning and defining a cohesive data platform architecture that seamlessly integrates data collection, transformation, and visualization. The successful candidate will spearhead the technological evolution of the architecture and data infrastructure over the data lakehouse to support business objectives.
* design, deploy, evolve, and ensure the integrity of the organization's official data platform layer, defining a roadmap for its utilization.
* develop and document the strategic roadmap for the evolution of the data architecture, collaborating with technical areas to gather improvement requirements.
* promote standards and guidelines for data architecture in projects.
* define the framework, guidelines, standards, and principles of data architecture platform, including modeling, metadata, security, backup, and reference data.
* continuously update data guidelines and standards, publishing and promoting them to relevant teams to ensure a unified and high-quality data design approach across the organization.
* evaluate and propose new technologies based on market best practices like real and near real-time data ingestion.
* identify improvement opportunities in data ingestion and define the interaction model between roles to ensure a proper data lifecycle.
* collaborate with cross-functional teams, including data engineering chapter lead, dataops lead, data modeling lead, data governance, and the it area to implement and maintain data pipelines supporting dataops practices.
* design comprehensive solutions such as the implementation of data marketplace, data sharing, and similar initiatives.
* ambassador of agile methodologies: drive the adoption and continuous improvement of agile development methodologies.
* continuous improvement: identify opportunities for process improvements and implement solutions to enhance efficiency.
the ideal candidate possesses extensive experience in similar positions and advanced knowledge of:
* cloud platforms or big data ecosystems in retail companies.
* aws/gcp/azure cloud services, including real-time events.
* databricks platform with focus on unity catalog, mlops, dataops, ai architecture, and advanced analytics.
* data integration tools and technologies for ingesting the data lakehouse with information from various sources.
* event hubs tools like apache kafka and cloud-native event tools.
* best practices in data security and governance.
familiarity with databricks' apis, unity catalog, data catalog tools, and api gateway.