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We are looking for a candidate who confidently knows and understands different technologies, is able to deliver data architecture designs and recommendations, supported by both high‑level and detailed documentation, as well as choose appropriate technologies and tooling, design data models and pipelines, and define clear implementation roadmaps with scaling considerations. We are looking for someone passionate about the opportunity to independently design and deliver data architecture solutions that directly address client requirements and business goals. If you are comfortable defining, executing, and validating proof‑of‑concepts (PoCs) across multiple industries and projects, keep reading below:
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