Solution Design Lead, Consultant

Your Role

The Data Services team is responsible for technical design and end-to-end delivery of complex data-driven solutions and data products for the enterprise. The Solution Design Lead, Consultant will report to the Sr Manager, Data Solutions / Director. In this role you will be partnering with Enterprise Architects, Portfolio, Analytics and Data engineering teams for designing technical solutions and building data products to meet enterprise data needs. You will be responsible for driving the data product by designing and implementing cloud data lakes, data warehouse and data mart solutions. If you have a passion for innovation with a data driven mindset and can-do attitude, we are looking for you.

Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow - personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.

Your Knowledge and Experience

• Requires a college degree or equivalent experience and a minimum of 10 years of relevant experience.
• Expert in understanding data management practices, data modelling (data vault 2.0), master data management, data integration, data architecture, data virtualization, data warehousing, data privacy and security.
• Hands on experience with SQL, Python, Collibra, Reltio Master Data Management, DBT Cloud and DBT core. Expert in one or more of NoSQL and database appliances and platforms (Snowflake, Synapse, Databricks)
• Prior experience in data product management is a must. This includes skills with creating roadmaps, converting business requirements to technical stories, feature prioritization and working collaboratively across cross-functional teams.
• Excellent Communication skills for engaging with stakeholders, facilitating discussions, and conveying complex technical concepts. Ability to lead and influence stakeholders while maintaining data quality standards and delivering a high-quality data product is desired.
• Advance knowledge in designing solutions for large data warehouses with a good understanding of cluster and parallel architecture.
• Adept in agile methodologies, such as Scrum or Kanban, is required for managing product backlog, sprint planning and facilitating agile development.
• Knowledgeable of Source Control and Project Management tools like Bitbucket, Git, and JIRA

Hybrid

This role requires employees to be in-office based on our hybrid workplace model, balancing purposeful in-person collaboration with flexibility. For most teams, this means coming into the office two days each week.

Employees living more than 50 miles from an office location will work with their manager to determine in-office time based on business need.

• #LI-FB1

Your Work

In this role, you will:

• Expert in driving strong collaboration with business and technology stakeholders to define product strategy, business, and technology requirements, use cases, and new capabilities.
• Develop and maintain technology inventory and definitions, including application reference models, guiding principles, standards, patterns, and usage guidelines.
• Design and implement cloud solutions. Ability to perform risk identification and mitigation. Able to provide issue management recommendations as required.
• Able to articulate best practices around advanced cloud-based solutions and provide advice on strategies for migrating existing workloads to the cloud.
• Able to provide recommendations on designing cost effective data infrastructure that supports complex data analytics services.
• Socialize and champion technology related ideas and plans with internal IT teams and business stakeholders.
• Exhibit thought leadership. Evangelize data and analytics solutions that benefit business stakeholders.
• Familiarity with DevOps best practices and automation of documentation, testing, build, deployment, configuration, and monitoring
• Work closely with data engineers and data analyst teams, utilizing agile methodologies to plan and prioritize product backlog.
• Partner with Portfolios to enable, architect, implement and define the technical requirements, principles and models that guide data solution decisions for on-prem, cloud and hybrid ecosystem
• Provide comprehensive analytical thinking to ensure time to market, cost impact and value are properly understood, estimated, and controlled across people, process, and technology.
• Monitor and analyze the performance of data product, identify areas of improvement or optimization to enhance the data product and its features

Your Work

In this role, you will:

• Expert in driving strong collaboration with business and technology stakeholders to define product strategy, business, and technology requirements, use cases, and new capabilities.
• Develop and maintain technology inventory and definitions, including application reference models, guiding principles, standards, patterns, and usage guidelines.
• Design and implement cloud solutions. Ability to perform risk identification and mitigation. Able to provide issue management recommendations as required.
• Able to articulate best practices around advanced cloud-based solutions and provide advice on strategies for migrating existing workloads to the cloud.
• Able to provide recommendations on designing cost effective data infrastructure that supports complex data analytics services.
• Socialize and champion technology related ideas and plans with internal IT teams and business stakeholders.
• Exhibit thought leadership. Evangelize data and analytics solutions that benefit business stakeholders.
• Familiarity with DevOps best practices and automation of documentation, testing, build, deployment, configuration, and monitoring
• Work closely with data engineers and data analyst teams, utilizing agile methodologies to plan and prioritize product backlog.
• Partner with Portfolios to enable, architect, implement and define the technical requirements, principles and models that guide data solution decisions for on-prem, cloud and hybrid ecosystem
• Provide comprehensive analytical thinking to ensure time to market, cost impact and value are properly understood, estimated, and controlled across people, process, and technology.
• Monitor and analyze the performance of data product, identify areas of improvement or optimization to enhance the data product and its features