Detailed JD below :
The Data Architect works in all data environments which includes data design, database architecture, metadata, and repository creation. The Data Architect work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action.
The Data Architect responsible for developing blueprints for all data repositories, evaluating hardware and software platforms, and integrating systems. Translates business needs into long-term data architecture solutions. Defines, designs, and builds dimensional database schemas. Evaluates reusability of current data for separate analyses. Conducts data sheering to rid the system of old, unused, or duplicate data. Reviews object and data models and the metadata repository to structure the data for better management and quicker access. Understands department, segment, and organizational strategy and operating objectives, including their linkages to related areas. Makes decisions regarding own work methods, occasionally in ambiguous situations, and requires minimal direction and receives guidance where needed. Follows established guidelines/procedures.
Data Architecture & Strategy
Define and maintain enterprise data architecture standards, principles, and roadmaps.
Design scalable data platforms supporting analytics, reporting, AI/ML, and operational workloads.
Develop conceptual, logical, and physical data models for enterprise applications.
Establish architecture patterns for data integration, master data management, and data quality.
Cloud Data Platform Leadership
Lead the design and implementation of cloud-based data platforms using technologies such as Snowflake, Prefect, Google Cloud Platform (Google Cloud Platform), Azure and Databricks
Define best practices for data storage, processing, orchestration, and security.
Guide migration of on-premises data assets to cloud environments.
Data Engineering & Integration
Architect batch, real-time, and event-driven data pipelines.
Design solutions for API integrations, ETL/ELT frameworks, and data virtualization.
Ensure high-performance and scalable ingestion, transformation, and consumption of data.
Governance & Compliance
Partner with Data Governance teams to establish metadata management, lineage, stewardship, and data quality frameworks.
Ensure compliance with regulatory requirements including HIPAA, PHI, SOC, and privacy policies.
Implement enterprise security and access control standards.
Stakeholder Collaboration
Collaborate with executive leadership, business teams, product owners, and engineering teams to translate business needs into technical solutions.
Provide architecture guidance and technical oversight throughout project lifecycles.
Present architecture strategies and roadmaps to senior leadership.
Thank you
