Sr. Data Architect

Job Description

The Senior Data Architect offers technical expertise and guides development teams to create innovative data architecture solutions to build meaningful data products and insights. The successful candidate will work closely with business and technology teams to understand business requirements, provide data architecture recommendations, define best practices, and reference architecture patterns for enterprise data assets. The ideal candidate should have extensive experience in modern data warehouse and Lakehouse development, including Cloud and data product architectures. Data modeling, ETL processes, and data governance knowledge is highly desirable. The ability to lead cross-team technical discussions and drive defined solutions to execution is highly desirable. As a Data Architect, you will collaborate with Enterprise, Cloud, Application, and Digital Architects and development teams to deliver cutting-edge solutions.

Duties and Responsibilities:

• Design and implement a scalable data lake house using Cloud data platforms like Snowflake, Google bigQuery and Redshift, which will enable efficient data storage, processing, and analytics across structured, semi-structured, and unstructured data sources.
• Work closely with business stakeholders, data scientists, data engineers, and IT teams to define data requirements, identify opportunities, and deliver high-quality data solutions.
• Have experience in modern data warehouse and Lakehouse development, including Cloud and data product architectures.
• Expert Knowledge of data modeling, ETL processes, and data governance is highly desirable.
• Expert knowledge of Business intelligence (BI), Dashboards and Analytics tools.
• Communicate effectively with both technical and non-technical stakeholders.
• Stay up to date with emerging technologies and trends in data architecture and make recommendations on their adoption.
• Participate in proof of concepts, analysis/design, assessing new technologies, identifying data trends, and performing complex data analysis and analytics.
• Collaborate with cross-functional teams, including business stakeholders, data scientists, data engineers, and IT teams, to define future data management architecture, aligning with value creation opportunities across the business.
• Help set design patterns for application integration, data governance, and analytics development.
• Provide enhancement and optimization with ETL/ELT process development and maintenance.
• Experience with workflow management systems like Apache Airflow, Orkes and AWS Step Functions can be useful for orchestrating complex data workflows and pipelines.
• Develop and implement data migration strategies.
• Develop and maintain data dictionaries, metadata repositories, and data lineage documentation.
• Stay up to date with emerging technologies and trends in data architecture.
• Proficiency in data formats such as JSON, HL7, EDI, and XML
• Proficiency in event-driven architecture and message queuing systems like NATS,Apache Kafka, Kinesis,IBM IIB and AWS SQS can be valuable for building scalable and resilient data architectures.
• Experience utilizing API development and integration using tools such as MuleSoft and REST APIs