Senior Data Architect

Translate high-level business requirements into data models, metadata, test data, and data quality standards.

Manage senior business stakeholders to ensure strong engagement and alignment with long-term strategic roadmaps.

Lead and participate in peer reviews and quality assurance of project architecture artifacts.

Define and manage standards, guidelines, and processes to ensure data quality.

Work with IT teams, business analysts, and data analytics teams to understand data consumers' needs and develop solutions.

Evaluate and recommend emerging technologies for data management, storage, and analytics.

Establish and maintain governance frameworks for internal teams and vendor partners to ensure effective architecture services.

Understanding data confidentiality, security, and compliance requirements and implementing data protection rules across storage, compute, and consumption layers.

Designing data protection solutions at database, table, column, and API levels based on enterprise security, privacy, and architecture standards.

Designing the structure and layout of data systems, including databases, data warehouses, and data lakes.

Selecting and implementing database management systems based on organizational requirements.

Defining data schemas, optimizing data storage, and establishing data access controls and security measures.

Enhancing data pipeline performance and ensuring timely orchestration.

Implementing and maintaining data governance standards across enterprise data platforms.

Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.

At least 10 years of relevant experience designing and implementing data models (Erwin) for enterprise data warehouse initiatives.

Experience leading projects involving cloud data lakes, data warehousing, data modeling, and data analysis.

Proficiency in modern data architecture and cloud services, particularly AWS.

Experience with real-time data distribution technologies such as Kinesis, Kafka, and Dataflow.

Experience with modern data warehouse platforms such as Redshift, Snowflake, and Databricks.

Experience with database platforms including DB2, MS SQL Server, PostgreSQL, Couchbase, and MongoDB.

Strong understanding of entity-relationship modeling, metadata systems, data security, and data quality tools and techniques.

Ability to design traditional relational and modern big-data architectures based on business requirements.

Experience with business intelligence tools and technologies such as Informatica, Power BI, and Tableau.

Exceptional communication and presentation skills.

Strong analytical and problem-solving abilities.

Ability to collaborate effectively with data scientists, business analysts, IT teams, and senior stakeholders.

Ability to guide solution design and enterprise architecture to meet business needs.