Data Architect - Staff Software Engineer

• →Define and maintain enterprise data architecture blueprints, reference architectures, and design standards across cloud-native data platforms.
• →Partner with Product Managers, Data Engineering leads, and Solution Architects to translate business requirements into scalable, future-proof data designs.
• →Lead the architecture and governance of data domains including data modelling, data mesh / data product design, and metadata management.
• →Define and enforce data modelling standards (conceptual, logical, physical) across relational, dimensional, and NoSQL stores.
• →Collaborate with Data Scientists and ML Engineers to architect feature stores, MLOps pipelines, and model-serving data layers.
• →Establish and govern data quality frameworks, lineage tracking, and cataloging standards across the platform.
• →Guide engineering teams on applying architectural patterns, data design principles, and platform conventions.
• →Conduct architecture reviews and provide design authority sign-off on high-impact data solutions.
• →Drive continuous improvement in data platform design, documentation, and reusability of architectural assets.
• →Work closely with security and compliance teams to embed data governance, access control, and regulatory standards into platform design.
• →Evaluate and recommend emerging technologies and architecture patterns that improve platform capabilities.

Must-have skills

• 9–11 years of experience in a Data Architecture or senior Data Engineering role, with at least 3 years in an architecture-focused capacity.
• Graduate degree in Computer Science, Information Systems, or equivalent.
• Strong analytical thinking, logical reasoning, and the ability to communicate complex architectural decisions to both technical and non-technical stakeholders.
• Hands-on expertise with cloud-native data architecture on:
  • Azure: Databricks, Data Lake Gen2, Unity Catalog, Azure SQL, Synapse Analytics, ADF
  • Or equivalent GCP stack: BigQuery, Dataflow, Cloud Composer, Dataplex, etc.
• Deep proficiency in data modelling —lakehouse / medallion architecture patterns.
• Experience designing data mesh or data product architectures — including domain ownership, data contracts, and self-serve data infrastructure.
• Strong knowledge of metadata management, data cataloging, and data lineage tools (e.g. Apache Atlas, Alation, DataHub, Unity Catalog).
• Proficiency in data quality and observability frameworks (e.g. Great Expectations, dbt tests, Monte Carlo).
• Experience with relational and non-relational databases, data streams, and file stores.
• Proficiency in Python and SQL for prototyping and validating architectural designs.
• Strong familiarity with version control and CI/CD tools (GitHub, Jenkins) in the context of DataOps and infrastructure-as-code.

Good-to-have skills

• Experience defining enterprise data governance frameworks including data stewardship models and data ownership policies.
• Familiarity with data privacy, regulatory compliance standards (GDPR, CCPA) and their architectural implications.
• Exposure to MLOps platforms and feature stores (Feast, Tecton, Vertex AI Feature Store).
• Knowledge of API design and enterprise integration patterns for data product exposure.
• Experience with reporting and BI tool integration (Power BI, Looker, MicroStrategy) at the platform architecture layer.
• Exposure to DevOps and observability practices including pipeline monitoring and data SLA management.
• Experience supporting business users and data product teams with architecture guidance and patterns.
• Strong documentation skills — ability to produce clear architecture decision records (ADRs), design diagrams, and platform standards documentation.
• Familiarity with infrastructure-as-code tools (Terraform, Bicep) for data platform provisioning.