Data Architect Lead
1 month ago
We are seeking an accomplished Data Architect to lead our team in designing, implementing, and maintaining data architecture solutions that drive business success and guarantee data integrity, security, and accessibility.
Key Responsibilities:
- Design and develop advanced conceptual, logical, and physical data organizations, models, repositories, dashboards, and reports within a comprehensive functional and technical architecture.
- Develop and implement sophisticated statistical models and machine learning algorithms to resolve complex business problems.
- Collaborate with other architects, infrastructure, and software experts to define metadata layers, technical strategies, and optimal integrations within the existing client IT landscape.
- Translate technical solutions into actionable plans, review proposed solutions, and optimize them as needed.
- Design, develop, and continuously improve supporting activities, such as automation of versioning and release management, scheduling, security models, and impact assessments 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 align with 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 continuous improvement for existing data pipelines, data models, reports, and infrastructure.
- Implement best practices for data, model management, and version control.
Qualifications:
A master's 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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