Data Architect

Quick Facts

• Role: Data Architect (cloud data platform architecture and delivery leadership)

Description

Lead the design of cloud data platforms for clients, owning the target architecture end-to-end from discovery to production. You will work directly with client stakeholders, guide engineering teams through delivery, and contribute to pre-sales with workshops, solution design, and architecture reviews. The role covers lakehouse/warehouse patterns, governance and security, legacy migrations, and platform cost/performance optimization.

Responsibilities

• Design end-to-end data architectures on Snowflake and/or Databricks on Azure and/or AWS (ingestion, storage, processing, serving, consumption)
• Define lakehouse and data warehouse patterns (medallion architecture, data vault, dimensional models) and select the right approach per use case
• Lead migrations from legacy platforms (on-prem DWH, Hadoop, Teradata, Oracle, SQL Server) to the cloud, including assessment, roadmap, and cutover plan
• Set standards for data modeling, pipeline design, CI/CD, infrastructure as code, and environment strategy
• Design data governance, security, and compliance: access control, data lineage, cataloging, and GDPR/local privacy law alignment
• Optimize platform cost and performance (warehouse sizing, cluster policies, FinOps practices)
• Run discovery workshops and architecture reviews with stakeholders in English
• Support pre-sales: solution design, effort estimates, technical sections of proposals, and client presentations
• Mentor data engineers; review designs and code; act as the technical escalation point
• Prepare data foundations for BI, advanced analytics, ML, and GenAI use cases

Requirements

• 8+ years in data engineering or data platforms, including 3+ years as a Data or Solution Architect
• Hands-on production experience with Snowflake and/or Databricks (at least one in depth)
• Strong knowledge of Azure and/or AWS data services (e.g., ADLS Gen2, Data Factory, Synapse/Fabric, Event Hubs, Purview, Key Vault; or S3, Glue, Redshift, Kinesis, Lambda, Lake Formation, IAM)
• Expert SQL and solid Python or Scala; experience with Spark
• Proven experience with data modeling (dimensional, data vault) and lakehouse design
• Experience with orchestration/transformation tools (Airflow, dbt, Azure Data Factory, Databricks Workflows)
• Working knowledge of infrastructure as code (Terraform, Bicep, CloudFormation) and CI/CD for data
• Track record leading at least one cloud data platform build or migration from design to production
• Client-facing consulting experience (workshops, architecture decision presentations, managing expectations)
• B2 English proficiency (written and spoken)

Benefits

Not specified in the provided posting.