Manager Data Architect
As a Manager Data Engineering (Data Architect), you will be responsible for designing and implementing scalable, high-performance data solutions that enable advanced analytics, machine learning, and business intelligence. You will work closely with cross-functional teams to define data architecture, optimize data pipelines, and ensure data quality and governance.
Your Impact
- Evaluate requirements and current state to design scalable architectures for enterprise data platforms, ensuring high performance, reliability, and cost effectiveness.
- Validate target-state designs with client technical SMEs and secure executive buy-in, translating architecture into roadmaps and business value.
- Lead efforts to improve data quality, data lineage, and master data management and establish best-practices for data governance, security, and compliance.
- Collaborate with data scientists, business analysts, and engineering teams to deliver data-driven solutions.
- Ensure seamless integration of data across cloud services (AWS, GCP, Azure), SaaS, and on-premise applications, with a variety of structured/unstructured formats.
- Develop data models and modelling standards across conceptual, logical, and physical layers, with metadata and data dictionaries to ensure consistency and accuracy.
- Provide technical leadership and mentorship to client and delivery teams, ensuring best practices and innovation.
- Effectively leverage AI to augment production of quality deliverables.
- Stay updated on emerging trends in AI, and cloud-based data solutions to drive continuous improvement and commercial advantage for our clients.
Skills & Experience
- 12+ years of experience in data engineering, with a focus on data technologies.
- Strong expertise in data architecture, data modeling, and ETL/ELT processes.
- Proficiency in cloud-based data solutions, including AWS, GCP, or Azure.
- Experience with real-time data processing using Kafka, Flink, or similar technologies.
- Strong understanding of data governance, security, and compliance frameworks.
- Knowledge of SQL, NoSQL databases, and data warehousing solutions.
- Experience with containerization and orchestration tools such as Docker and Kubernetes.
- Excellent problem-solving and analytical skills with a strong focus on performance optimization.
Set Yourself Apart With
- Experience with AI/ML data pipelines and model deployment.
- Knowledge of graph databases and data virtualization.
- Strong understanding of data mesh and modern data architecture principles.