Topgolf Callaway Brands is an unrivaled tech-enabled Modern Golf and active lifestyle company while also being a great place to work. With a portfolio of global brands including Topgolf, Callaway Golf, TravisMathew, Toptracer, Odyssey, OGIO, Jack Wolfskin, and World Golf Tour (“WGT”), we have a team of passionate individuals who dare to be great while acting with integrity and respect. We stay hungry, yet humble. All while having fun and making golf accessible and enjoyable for everyone!
Our company is a blend of experience and diverse backgrounds, and our leaders have a strong history of building and selling successful initiatives. We are working to build a truly groundbreaking company, and we want top-notch people to join us in that mission.
A Senior Principal Business Intelligence Architect is a senior position within the Enterprise Data Analytics team that focuses on the architectural aspects of BI systems. This role involves designing and implementing the overall BI architecture, data integration processes, and analytics solutions for Topgolf-Callaway.
As a Sr. Principal Architect, your role will be to ensure that we are at the bleeding edge of technology, at the forefront of using the modern principles and tools, software and applications in the business to meet our strategies. You will also ensure that we are following the best practices for optimal efficiency. This role will be a thought leader in our journey to modernize our data platforms and ensure maximum adoption. This role will report to and work closely with the Head of Enterprise Analytics and Data Engineering as well as other leaders and engineers within the Data organization.
ROLES AND RESPONSIBILITIES
· Architectural Design: Developing the overall BI architecture that aligns with the organization's strategic goals and objectives. This includes designing data warehouses, data marts, ETL processes, and reporting and analytics platforms.
· Data Integration: Defining and implementing data integration strategies to collect, transform, and load data from various sources into the BI systems. This involves selecting and configuring appropriate ETL tools, establishing data integration standards, and ensuring data quality and consistency.
· Data Modeling: Designing data models and structures to support efficient data analysis, reporting, and visualization. This includes conceptual, logical, and physical data modeling to ensure the integrity and usability of data within the BI systems.
· Solution Evaluation and Selection: Assessing and selecting appropriate technologies, tools, and platforms for BI implementation. This involves evaluating vendor solutions, conducting proof of concepts, and recommending the most suitable options based on business requirements and technical considerations.
· Collaboration and Stakeholder Management: Collaborating with business stakeholders, data analysts, data scientists, and other IT teams to gather requirements, understand business needs, and translate them into technical solutions. Building strong relationships with stakeholders and effectively communicating the architectural vision and strategy.
· Performance Optimization and Scalability: Optimizing the performance and scalability of BI systems by implementing efficient data retrieval and processing techniques. Identifying and addressing performance bottlenecks and ensuring that the BI infrastructure can handle increasing data volumes and user demands.
· Data Governance and Security: Establishing and enforcing data governance policies, standards, and best practices within the BI architecture. Ensuring data security, privacy, and compliance with regulatory requirements. Implementing access controls and data protection measures.
· Improvement and adopting Emerging Technologies: Staying updated with the latest trends, advancements, and emerging technologies in the BI field. Evaluating new tools, techniques, and methodologies that can enhance the BI architecture and deliver more value to the organization.
· Authoring whitepapers: There is an expectation of incessant innovation to ensure that we are on a path of constant improvement. All new innovations should be formalized in the form of whitepapers and/or patents.
TECHNICAL COMPETENCIES (Knowledge, Skills & Abilities)
· Extensive knowledge of modern database technologies like Snowflake, Azure Synapse or AWS Redshift with Snowflake being the preferred option
· Deep understanding of cloud architecture on Azure technologies
· Universal experience in all aspects of data engineering fundamentals
· Exposure to large volume data processing at scale and rapid speed of ingestion
· Development experience in leading POCs for new tool procurement
· Experience in formulating CI/CD DevOps as well as MLOps strategies
· Familiarity with AI/ML concepts such as OCR, NLP as well as experience on software such as Dataiku, Databricks etc. is preferred.
EDUCATION AND EXPERIENCE
· Bachelor's degree (B.S. or B.A.) or equivalent experience in a STEM discipline
· Snowpro or higher certification is preferred.
· Certification in Cloud Architecture from any of the 3 major cloud providers is a distinct advantage
· A minimum of 6+ years of experience as an architect in a data organization
· Experience in working across geographies across multiple time zones is required