Job Description

Responsibilities

• Participates in planning, definition, and high-level design of data solutions, exploring alternatives and evaluating new technologies.
• Develops and maintains scalable cloud-based data infrastructure, ensuring alignment with the organization's decentralized data management strategy.
• Designs and implements ETL pipelines using AWS services (e.g., S3, Redshift, Glue, Lake Formation, Lambda) to support data domain requirements and self-service analytics.
• Collaborates with data domain teams to design and deploy domain-specific data products, adhering to organizational standards for schema design, data transformations, and storage solutions.
• Establishes and enforces data governance practices, including compliance with data privacy, access controls, and lineage requirements, across the organization’s data assets.
• Maintains a comprehensive data catalog and governance tools, automating workflows to uphold data integrity and ensure discoverability across all domains.
• Leads the implementation and ongoing support of data mesh architecture, ensuring seamless integration and data flow across multiple domains.
• Ensures the availability and reliability of the organization’s Data Mesh software, managing operations and maintenance of the framework.
• Provides guidance and leadership on the cultural adoption of data mesh principles, including organizational training initiatives for data stewards and users.
• Communicates effectively with stakeholders to align technical data architecture with business goals, ensuring long-term support for analytics, insights, and innovation.
• Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe.
• Provide team specific training as needed.

Qualifications and Experience:

• Experience in Data Architecture: Minimum of eight (8) years of experience designing and implementing data architectures, including large-scale data environments such as data lakes, data warehouses, and data mesh frameworks.
• Experience with Cloud Platforms: Minimum of five (5) years of experience working with cloud-based data platforms (e.g., AWS, Azure, Google Cloud), particularly for data storage, processing, and analytics.
• Leadership and Team Management: Demonstrated two (2) years of experience leading and mentoring data engineering teams, fostering collaboration, and ensuring successful project execution.
• Education: A bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or a related technical field, preferred.