Data Platform Architect
- Deeplight
- Dubai - United Arab Emirates
- Full-time
وصف الوظيفة
About DeepLight AI
DeepLight is a pioneering AI company committed to pushing the boundaries of innovation in artificial intelligence. Our mission is to harness the power of data and machine learning to revolutionize industries and create a brighter future. With a dynamic team of experts and a culture of relentless innovation, we are at the forefront of AI research and development.
Position Overview
We are seeking a visionary and experienced Senior Data Platform Architect to join our leadership team. In this role, you will be responsible for defining the strategic vision and architectural direction of our enterprise-grade data platforms that power our AI solutions. You will lead the design of complex data ecosystems, drive architectural decisions across multiple teams, and establish the technical foundation for our next-generation AI capabilities.
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إمتيازات الوظيفة
Impact: Be part of a dynamic team that is shaping the future of AI and making a meaningful impact on industries and society.
Innovation: Work on cutting-edge projects at the intersection of AI, data engineering, and machine learning, leveraging the latest technologies and methodologies.
Collaboration: Collaborate with a diverse team of experts from various disciplines, fostering creativity, learning, and growth.
Opportunity: Enjoy ample opportunities for professional development, career advancement, and leadership roles in a rapidly growing company.
Culture: Join a culture of curiosity, excellence, and collaboration, where your ideas are valued, and your contributions are recognized and rewarded.
If you are passionate about data architecture, AI, and innovation, and you thrive in a dynamic and collaborative environment, we want to hear from you! Apply now to join DeepLight and be part of our journey to unlock the potential of AI for a brighter future.
متطلبات الوظيفة
Key Responsibilities
- Define and execute the strategic roadmap for enterprise data platform architecture, ensuring alignment with business objectives and long-term scalability goals
- Design comprehensive data architecture blueprints that support multi-petabyte scale AI workloads and real-time analytics across diverse business domains
- Lead cross-functional architecture reviews and provide technical guidance to engineering teams on complex data platform implementations
- Establish architectural standards, design patterns, and best practices for data platform development across the organization
- Collaborate with executive leadership, product managers, and data scientists to translate business requirements into scalable technical architectures
- Evaluate and recommend emerging technologies, conducting proof-of-concepts to assess their strategic value for our data platform evolution
- Drive the architectural decisions for data mesh implementations, ensuring seamless integration across distributed data domains
- Mentor and develop senior engineers and architects, building organizational capabilities in advanced data architecture concepts
- Lead the design of fault-tolerant, self-healing data systems that ensure 99.99% availability for mission-critical AI workloads
- Establish data platform security architecture and compliance frameworks that meet enterprise and regulatory requirements
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field; advanced degree preferred
- 10+ years of experience in data platform engineering and architecture, with demonstrated experience leading large-scale enterprise implementations
- Proven track record of architecting and delivering complex data platforms supporting AI/ML workloads at scale (petabyte+ datasets)
- Deep expertise in multi-cloud architecture design and implementation across AWS, Azure, and GCP
- Advanced proficiency in multiple programming languages including Python, Java, Scala, and SQL
- Extensive experience with distributed computing frameworks and big data technologies (Hadoop, Spark, Flink, Kafka)
- Strong background in data modeling, dimensional modeling, and modern data warehouse architectures (Snowflake, BigQuery, Redshift)
- Experience with container orchestration platforms (Kubernetes) and infrastructure-as-code (Terraform, CloudFormation)
- Deep understanding of data governance frameworks, data lineage, and metadata management at enterprise scale
- Experience with event-driven architectures and real-time streaming platforms
