Data Architect

Description of Duties:

At eimagine, we know that your best work happens when you live your best life and share your unique talents, so we do everything we can to be intentional in a remote enabled environment to make that possible.  Recognized as a Best Places to Work since 2015, we are a team of humbly confident people who are proud of their craft, continuous learners, and have been known to cheer loudly for our teammates. For over 25 years we have been helping clients navigate technology and business change, while staying committed to delivering value & outcomes that enables their success.  

Due to our growth, we are seeking a Data Architect. The Data Architect is responsible for designing, developing, and managing the overall data architecture strategy for an organization. They create blueprints for data management systems to integrate, centralize, protect, and maintain data sources. Working with various technologies, including Azure, AWS, Google Cloud, and Snowflake, they ensure that data solutions align with business goals and support advanced analytics capabilities. In addition to sharing our enthusiasm for team collaboration (we promise our secret handshake isn’t hard to learn), you have an unmatched passion for using technology to solve problems and fulfill business outcomes.

This is a remote enabled position.

Description of Duties:

• Design and implement a comprehensive data architecture strategy aligned with business objectives.
• Develop data models, database designs, and data integration solutions to support business intelligence and analytics initiatives.
• Create and maintain data standards, policies, and procedures to ensure data quality, consistency, and governance across the organization.
• Collaborate with cross-functional teams to understand data requirements and translate them into scalable architectural solutions.
• Lead the evaluation and selection of data management technologies and tools, with a focus on Azure and other cloud platforms (AWS, Google Cloud, Snowflake).
• Design and implement data security and privacy measures to ensure compliance with regulations and industry standards.
• Develop and maintain data flow diagrams, entity-relationship diagrams, and other architectural documentation.
• Optimize data architecture for performance, scalability, and cost-efficiency.
• Guide the implementation of data warehouses, data lakes, and other big data solutions.
• Mentor and provide technical leadership to data engineers and other team members.
• Stay current with emerging trends and technologies in data architecture and analytics.
• Collaborate with data science teams to ensure the architecture supports advanced analytics and machine learning initiatives.
• Develop strategies for data integration, including ETL/ELT processes and real-time data streaming.
• Implement metadata management and data lineage tracking systems.
• Lead data architecture reviews and assessments to identify areas for improvement.
• Participate in capacity planning and resource allocation for data infrastructure.
• Develop and maintain disaster recovery and business continuity plans for data systems.
• Collaborate with project managers to ensure data architecture aligns with project timelines and deliverables.
• Provide expertise in resolving complex data-related issues and challenges.
• Participate in and often lead architectural design reviews and technical steering committees.
• Contribute to the development of data governance frameworks and best practices.
• Utilize cloud-based tools and services, particularly within the Azure ecosystem, to implement and manage data solutions.
• Ensure compliance with data privacy regulations such as GDPR, CCPA, and industry-specific requirements.
• Participate in prescribed Agile ceremonies and support the implementation of DevOps practices for data solutions.
• Maintain professional development through relevant certifications (e.g., Azure Data Engineer, AWS Certified Data Analytics, Google Cloud Professional Data Engineer).
• Responsible for timely and accurate time entry and project documentation.
• Lead the technical evaluation of data architecture components for RFP responses, ensuring proposed solutions meet client requirements and industry best practices.
• Collaborate with sales and pre-sales teams to develop comprehensive data architecture proposals for RFPs, including solution design, technology stack recommendations, and implementation strategies.
• Prepare detailed technical documentation and architectural diagrams to support RFP submissions, clearly articulating the proposed data solutions and their benefits.
• Conduct feasibility assessments and risk analyses for proposed data solutions in RFP contexts, considering factors such as scalability, integration complexity, and long-term maintainability.
• Participate in client meetings and presentations to explain proposed data architectures and address technical questions during the RFP process.
• Stay informed about competitors' data solution offerings to ensure our RFP responses are competitive and innovative.

• 5+ years of experience in data architecture or related field
• Azure Data Engineer Associate, AWS Certified Data Analytics, or Google Cloud Professional Data Engineer certification within 1 year
• Extensive experience in data modeling and database design
• Proficiency with Azure Cloud services
• Experience with ETL/ELT processes and data integration tools
• Familiarity with big data technologies (e.g., Hadoop, Spark)
• Proficiency in SQL and at least one programming language (e.g., Python, Java)
• Knowledge of data governance principles and practices
• Proficiency in other cloud data platforms (AWS or Google Cloud) preferred
• Multiple cloud platform certifications (Azure, AWS, Google Cloud) preferred
• Experience with modern data warehousing solutions (e.g., Snowflake, Redshift) preferred
• Understanding of machine learning concepts and their data requirements preferred
• Experience with data visualization tools (e.g., Power BI, Tableau) preferred
• Excellent verbal and written communication skills
• Excellent collaboration skills
• Strong analytical and problem-solving skills

• Master's degree in Computer Science, Data Science, Information Systems, or related field; Bachelor's degree with equivalent experience