Data Architect – Enterprise Data Platform & Integration

About the role

We are looking for a Data Solutions Architect to lead the design and implementation of an enterprise‑wide data platform. You will define data flows, ensure interoperability across tools, and build a scalable, secure, and modern data environment that supports real‑time analytics and AI/ML initiatives.

Key responsibilities

• Define and evolve the architecture of data lakehouses, data meshes, and hybrid cloud solutions.
• Architect core data components from ingestion and processing to storage and APIs.
• Integrate platforms such as Databricks, Snowflake, Confluent, and Atlan into a unified ecosystem.
• Establish standards for scalability, resilience, and cost optimization.
• Design integration frameworks for ERP, POS, e‑commerce, CRM, and MarTech systems, covering batch, streaming, and API‑driven patterns.
• Collaborate with application architects to ensure seamless cross‑platform data exchange.
• Embed security, privacy, and compliance controls (encryption, tokenization, access control) into all integrations.
• Partner with governance teams to enforce metadata management, data lineage, and auditability.
• Mentor engineering teams on best practices for platform usage, API management, and event‑driven architectures.
• Assess emerging tools and lead modernization initiatives for AI/ML readiness and cost optimization.

Required profile

• 5+ years of experience in data engineering, solutions architecture, or platform integration.
• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related field.
• Proven ability to balance complex technical design with business needs.

Required skills

• AWS cloud platform
• Databricks, Snowflake, Kafka/Confluent, Delta Lake
• Integration patterns: ETL, ELT, CDC, APIs, streaming
• Data orchestration tools: Dagster, Airflow, dbt
• Data security techniques: encryption, tokenization, access control