Platform Architect
4 weeks ago
Role Summary
We are seeking an experienced Data Architect to join our team. The ideal candidate will have a strong background in designing, implementing, and maintaining data architecture solutions that support our business goals and ensure data integrity, security, and accessibility
Key Responsibilities:
Design advanced conceptual, logical and physical data organizations, models, repository, dashboards, reports within a complete functional and technical architecture.
Develop and implement advanced statistical models and machine learning algorithms to solve business problems.
Partner with other architects, infrastructure and software experts to define metadata layers, technical strategy and optimal integration within existing client IT landscape.
Translate to technical designers or developers designed solution, review proposed solution and optimize it when required.
Design, develop and continuously improve supporting activities (automation of versioning and release management, scheduling, security models, impact assessment of new changes )
Be accountable for the end-to-end solution.
Project Leadership:
Lead data projects from conception to deployment.
Coordinate with cross-functional teams, including product, engineering, and business stakeholders, to ensure successful project delivery.
Define project scope, goals, and deliverables that support business objectives.
Mentorship and Collaboration:
Mentor and provide guidance to data specialists.
Foster a collaborative and innovative team environment.
Communicate complex technical concepts and insights to non-technical stakeholders.
Research and Development:
Stay current with the latest advancements in data architecture and the broader data and AI landscape.
Experiment with new tools, techniques, and technologies to continuously improve data processes and analytics.
Deployment and Maintenance:
Oversee deployment and monitoring of data solutions in production environments.
Ensure that there is continuous improvement for existing data pipelines, data models, reports and infrastructure.
Implement best practices for data, model management and version control.
Qualifications:
Masters or Ph.D. degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
Experience:
5+ years of experience in data architecture, data engineering, or a related field.
Proven experience leading data projects and managing teams.
Extensive experience with big data platforms (cloud and on-premise), data modeling, data analysis, statistical modeling, and machine learning.
Technical Skills:
Proficiency in programming languages such as Python, R, or Scala.
Expertise in data processing frameworks like Apache Spark, Hadoop, or similar.
Proficiency with data modeling tools.
Strong SQL skills and experience with relational and NoSQL databases.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Advanced knowledge of data visualization tools like Tableau, Power BI, or similar.
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