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Company

ExamRoom.AI® · 11 hours ago

Data Architect

USA

Full-time

Remote

Senior Level

7+ years exp

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Artificial Intelligence (AI)E-Learning

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Responsibilities

Define and document the organization's data architecture vision, strategy, and principles.

Collaborate with business stakeholders and technical teams to understand data requirements and translate them into robust data architecture solutions.

Develop conceptual, logical, and physical data models to support data integration, storage, and retrieval.

Design data flows, data pipelines, and data transformation processes to enable efficient data movement and processing.

Develop and maintain data models that represent the organization's data assets and support business requirements.

Design and optimize relational and non-relational database schemas for performance, scalability, and data integrity.

Define data standards and naming conventions to ensure consistency and uniformity across databases.

Collaborate with database administrators and developers to implement and maintain databases and data structures.

Establish data governance policies, processes, and frameworks to ensure data quality, privacy, and compliance.

Define data classification, access controls, and data retention policies in collaboration with security and compliance teams.

Implement data protection measures, such as encryption, data masking, and anonymization techniques.

Monitor data usage and access patterns, identifying and mitigating data security risks.

Design and implement data integration strategies and solutions to facilitate seamless data flow across systems.

Develop Extract, Transform, Load (ETL) processes and workflows to extract data from various sources, transform it to meet business requirements, and load it into target systems.

Identify and implement data integration patterns, including real-time and batch processing, data synchronization, and data replication.

Ensure data quality and consistency throughout the integration process.

Collaborate with business intelligence and analytics teams to define data requirements for reporting, dashboards, and data visualization.

Design data marts, data warehouses, and data lakes to support analytics and reporting needs.

Develop data models and structures optimized for analytical processing and query performance.

Implement data aggregation, summarization, and transformation techniques to enable efficient analytics.

Collaborate closely with cross-functional teams, including business stakeholders, data scientists, developers, and infrastructure teams, to ensure alignment of data architecture with business goals.

Communicate complex data concepts and solutions to non-technical stakeholders in a clear and concise manner.

Participate in project planning, requirements gathering, and technical discussions.

Provide guidance and mentorship to junior data team members.

Qualification

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Data architectureData modelingSQLAWSETL processesDatabase designData integrationNoSQL databasesData governancePostgresSQL Server MaintenanceBig data technologiesData privacy regulationsData modeling tools

Required

Bachelor's degree in computer science, Information Systems, or a related field (relevant experience may substitute for formal education)

Minimum of 7 years of professional experience in data architecture or related roles

Proven experience in designing and implementing data architecture solutions, including data models, database design, and data integration strategies

Strong expertise in relational databases, SQL, and database design principles

Minimal exposures on cloud Techstacks - AWS/Azure ADFs – Preferably in AWS ETLs Glue and Warehouse/database – AWS Redshift

7+ years of experience on SQL Server Instance Maintenance or advance SQL query engine tuning (Trino) or Postgres

Familiarity with NoSQL databases, data lakes, data warehouses, and 5+ years of experience with big data technologies

7+ years of experience with data integration tools and technologies (e.g., ETL, ELT, data integration platforms)

Knowledge of data governance principles, data privacy regulations, and best practices

Proficiency in data modeling tools and techniques

Ability to read and comprehend instructions, correspondence, and memos

Ability to write moderately complex correspondence

Ability to effectively converse and present information in one-on-one and small group situations to customers, clients, and other employees of the organization