• Create and maintain optimal data pipeline architecture. • Assemble large, complex data sets that meet functional / non-functional business requirements. • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater performance and scalability, etc. • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies. • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. • Keep our data separated and secure across national boundaries through multiple data centers and AWS regions. • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. • Work with data and analytics experts to strive for greater functionality in our data systems.

• Design and implement a cost allocation rule engine supporting: Tag-based attribution, Account/subscription-based mappings, Custom business-defined allocation rules • Build amortization models for upfront cloud commitments: 1-year and 3-year reservations, Prepaid and committed-use discounts • Implement shared cost distribution models, including: Proportional allocation, Even split, Fixed-coefficient weighting • Create attribution logic for untagged costs, leveraging: Account ownership, Usage heuristics, Business metadata • Develop budget vs. actual variance models to support cost governance • Design forecasting input models using historical trends and seasonality • Ensure all models align with accounting principles, including: Period alignment, Matching principle, Accrual and amortization logic

• Function as a technical leader and advisor within the data technology field at TCGplayer, nurturing the growth and progress of both the company and individual engineers • Provide technical expertise and insight as you work with other teams to develop data flow strategies and define storage needs for microservices, ensuring scalability, reliability, and alignment with system architecture • Manage cross-application projects for datastores, emphasizing security, software currency, data governance, and platform migrations • Research emerging capabilities in both the datastores used by the organization and the broader marketplace to inform long-term strategic planning in the data domain • Consult on database design for the structures within an application’s datastores and queries/aggregations against those structures, optimizing for performance and scalability • Write minimal yet effective code, primarily database queries to facilitate data management and manipulation and proof-of-concepts for suggested techniques • Guide selection of appropriate datastore technologies for new and re-platformed apps, focusing on transactional microservices and event-driven systems to meet current and future data needs

• Lead data migration analyst and data migration efforts • Oversee the preparation of complex data queries; Extraction, Transformation, and Load (ETL), data cleansing • Prepare complex data analysis including trends, links, patterns, and an anomaly analysis • Provide data migration planning, strategy, assessment and analysis support to IT AD and delivery partners • Provide data migration testing and validation support designing and executing comprehensive testing strategies • Provide data migration execution and support to IT AD, business partners, stakeholder management • Provide continuous improvement of data migration activities to IT AD and business partners • Optimize data migration activities to resolve performance concerns • Identify areas for business process improvement and reengineering which will alter the data set and impact data migration