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Data & AI Architect

Discussion
  • Design and propose changes to current data systems including migration paths and modernization strategies for legacy architectures
  • Define and evolve the target architecture for data platforms covering ingestion, storage, processing, and consumption layers
  • Design and implement both batch and streaming/event-driven architectures to support diverse data processing requirements
  • Evaluate and recommend technology stacks across Azure, AWS, GCP and on-premises environments for hybrid and multi-cloud deployments
  • Design scalable, high-throughput data pipelines capable of handling large data volumes with low latency
  • Architect and deliver reporting systems using Power BI, Apache Superset, Grafana, or Tableau
  • Translate business and product requirements into technical architecture, data models, and implementation blueprints
  • Lead PoC design, implementation, and validation including architecture documentation
  • Assess AI/ML readiness including data availability, quality, governance, and infrastructure constraints
  • Ensure alignment with security, compliance, and regulatory standards including GDPR, SOC 2, ISO 27001, HIPAA, and PCI-DSS across all deployment environments
  • Collaborate closely with Product Managers, Engineers, and Domain Experts
  • Provide technical guidance during the transition from architecture to implementation
  • Strong experience in designing robust data systems from scratch including greenfield architecture definition, technology selection, and end-to-end implementation planning
  • Experience in modernization of data legacy systems
  • Hands-on experience with high-throughput data systems and performance optimization at scale
  • Multi-cloud experience across Azure, AWS, GCP, and including hybrid and on-premises deployments
  • Experience with AI/ML production systems
  • Experience implementing Lakehouse architecture with Apache Iceberg
  • Experience with modern data platforms such as Databricks and Snowflake
  • Solid understanding of batch architectures (ETL/ELT, data warehouses) and streaming architectures (Kafka, Flink or equivalent)
  • Experience designing reporting systems with BI tools (Power BI, Superset, Grafana)
  • Strong knowledge of relational databases, columnar stores, object storage, data catalogs, and orchestration tools (Airflow, dbt)
  • Familiarity with compliance frameworks and regulatory requirements: GDPR, SOC 2 Type II, ISO 27001, HIPAA, PCI-DSS, and data residency requirements
  • Experience implementing data governance controls, audit logging, access management, and encryption standards aligned to compliance mandates
  • Ability to bridge business and technical stakeholders and communicate architecture decisions clearly
  • Experience in public safety, critical infrastructure, or mission-critical systems
  • Exposure to real-time data processing and event-driven architectures

See also

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