Senior Data Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Establish and uphold data architecture standards, principles, patterns, and best practices across essential business and data domains.

• Evaluate and streamline critical data sources based on their business value, quality, ownership, usage, sensitivity, lifecycle, and strategic significance.

• Create conceptual, logical, and physical data models that facilitate operational systems, analytical platforms, reporting, data products, and integration requirements.

• Develop reusable data structures, canonical data models, reference data patterns, and integration strategies to enhance consistency across systems.

• Define architectural patterns for data ingestion, transformation, storage, consumption, sharing, retention, and lifecycle management.

• Collaborate with data engineering teams to implement architecture into scalable pipelines, curated datasets, data marts, reusable services, and platform-ready data assets.

• Promote standards for metadata, lineage, business definitions, data ownership, data quality rules, documentation, and data observability.

• Assist in governance practices by defining how data should be classified, secured, cataloged, retained, and accessed.

• Collaborate with application and platform teams to enhance interoperability across source systems, APIs, data warehouses, data lakes, lakehouses, and cloud platforms.

• Advise teams on designing reusable and trustworthy data assets that accommodate various consumption patterns, including reporting, analytics, automation, machine learning, and AI-enabled solutions.

• Offer architectural guidance during solution design, data quality assessments, platform modernization, and data integration projects.

• Clearly communicate architectural decisions, trade-offs, standards, and design recommendations to technical teams and senior stakeholders.

• Perform additional duties as assigned.

⛳️ Requirements

• Bachelor's degree with 7+ years (or Master's degree with 5+) of relevant experience in data architecture, data modeling, data engineering, data integration, analytics architecture, or related data fields.

• Extensive experience in designing data architectures for operational systems, analytical platforms, data warehouses, data lakes, lakehouses, and cloud-based data environments.

• In-depth knowledge of data modeling techniques, including conceptual, logical, and physical modeling, dimensional modeling, canonical modeling, and domain-oriented modeling.

• Proven ability to design reliable, governed, and reusable data assets for business operations, reporting, analytics, data integration, and data product use cases.

• Strong understanding of data quality, metadata management, lineage, cataloging, master data, reference data, and access control practices.

• Experience in defining architectural patterns for batch, near-real-time, API-driven, and event-driven data integration.

• Familiarity with modern cloud and data platforms such as Snowflake, Databricks, Azure, AWS, GCP, Informatica, dbt, or similar technologies.

• Ability to collaborate effectively across data engineering, application, analytics, security, governance, AI/ML, and business teams.

• Excellent communication skills with the capacity to explain complex data concepts to senior technical and business stakeholders.

• Capability to balance long-term architectural vision with practical implementation advice.

• Experience in creating architectural artifacts such as data flow diagrams, domain models, source-to-target mappings, architecture decision records, and data standards documentation.

🏝️ Benefits

• Equity grant

• Bonus eligible