Role Overview:The Senior Cloud Data Architect is a hands-on role responsible for designing, evolving, and optimizing the organization's cloud-based data architecture. This individual will shape the technical foundation for scalable, secure, and well-governed data systems that power analytics, AI, and enterprise intelligence. As an individual contributor, the architect partners closely with data engineers, analysts, product teams, and cloud specialists to design end-to-end solutions-spanning ingestion, transformation, storage, metadata, and consumption. The ideal candidate brings deep technical expertise in data architecture, metadata design, and cloud-native data services, coupled with a keen ability to translate complex requirements into elegant, maintainable designs.
Key Responsibilities:- Architect and optimize cloud-based data lakehouse and warehouse solutions that support analytics, machine learning, and enterprise integration needs.
- Define scalable and reusable data frameworks for ingestion, curation, transformation, and consumption.
- Evaluate and integrate Azure cloud services (e.g., Databricks, Data Lake, Event Hubs) to deliver high-performance data solutions.
- Implement architectural standards that ensure consistency, interoperability, security, and compliance across the data environment.
- Partner with engineering and business stakeholders to align architectural decisions with organizational objectives and KPIs.
- Drive architectural reviews, proof-of-concepts, and recommendations for future-state cloud data patterns.
- Design and operationalize metadata-driven architectures that improve discoverability, lineage tracking, and data quality monitoring.
- Collaborate with governance and engineering teams to implement active metadata approaches, enabling dynamic data cataloging and lineage visibility across pipelines.
- Define and enforce standards for metadata capture, schema management, and classification in alignment with enterprise data governance policies.
- Integrate data catalog tools and frameworks (e.g., Unity Catalog, Purview, or Collibra) with cloud ecosystems for automated metadata flow.
- Ensure consistent application of metadata structures across ingestion, transformation, and consumption layers.
- Produce detailed architecture artifacts, including data flow diagrams, system blueprints, and logical/physical data models.
- Communicate technical concepts clearly through visualization tools like Lucidchart, Visio, or Draw.io.
- Maintain robust documentation of architecture decisions, integration patterns, and system dependencies.
- Support cross-functional collaboration by sharing architecture roadmaps and data lineage documentation.
- Contribute to the design and implementation of distributed data pipelines using Databricks, and Spark.
- Apply advanced optimization principles for performance, cost, and scalability across compute and storage layers.
- Troubleshoot data latency, integrity, and transform issues across multi-environment pipelines.
- Implement modernization best practices such as CI/CD automation, schema evolution management, and pipeline observability.
- Partner with DevOps and platform teams to ensure maintainability and resilience of deployed solutions.
Required Skills:- 7+ years of professional experience in data engineering, architecture, or enterprise analytics platforms, including at least 3+ years focused on cloud data architecture.
- Proven experience designing and implementing Azure-based data solutions, including Data Lake, Data Factory, Synapse, and Databricks.
- Strong understanding of data modeling, schema design, and metadata management within large-scale data platforms.
- Hands-on expertise with distributed data processing frameworks such as Spark and Databricks.
- Demonstrated ability to produce and maintain clear architectural documentation and system diagrams.
- Proficiency in Python and SQL for pipeline development, data transformation, and automation.
- Analytical Mindset: Excels at identifying patterns, dependencies, and optimization opportunities within complex systems.
- Technical Communication: Skilled at documenting and explaining architectural decisions with clarity and precision.
- Collaboration: Works effectively across engineering, data governance, and cloud infrastructure teams without formal leadership responsibilities.
- Execution Focus: Takes ownership of technical outcomes, ensuring architectural integrity from concept to production.
Qualifications:- 4-year Bachelor's degree in Computer Science (strict requirement).
Preferred Skills:- Experience implementing metadata catalogs and governance platforms (e.g., Unity Catalog, Purview, DataHub, or Collibra).
- Proficiency with data lineage automation, provenance frameworks, and schema evolution tracking.
- Familiarity with active metadata and modern data orchestration ecosystems (e.g., Airflow, dbt).
- Knowledge of data security design patterns (e.g., encryption, RBAC, data masking).
- Exposure to multi-cloud or hybrid architecture patterns integrating on-premise and cloud systems.
- Understanding of medallion data architectures and modular data ingestion frameworks in large-scale deployments.
