• Design and implement a scalable data warehouse or data lakehouse to support analytics, reporting, and business KPIs • Develop and maintain reliable batch and/or streaming data pipelines from internal databases and external systems • Collaborate with stakeholders to translate business requirements into efficient data models and schemas • Establish and maintain data modeling standards and best practices • Implement monitoring, data quality controls, and observability for all data workflows • Provide well‑structured datasets to enable self‑service analytics for BI and data teams • Document the data platform, including lineage, definitions, and contracts, to create a shared source of truth for metrics

• Design and implement data pipelines to be processed and visualized across a variety of projects and initiatives • Develop and maintain optimal data pipeline architecture by designing and implementing data ingestion solutions on AWS using AWS native services • Design and optimize data models on AWS Cloud using Databricks and AWS data stores such as Redshift, RDS, S3 • Integrate and assemble large, complex data sets that meet a broad range of business requirements • Read, extract, transform, stage and load data to selected tools and frameworks as required and requested • Customizing and managing integration tools, databases, warehouses, and analytical systems • Process unstructured data into a form suitable for analysis and assist in analysis of the processed data • Working directly with the technology and engineering teams to integrate data processing and business objectives • Monitoring and optimizing data performance, uptime, and scale; Maintaining high standards of code quality and thoughtful design • Create software architecture and design documentation for the supported solutions and overall best practices and patterns • Support team with technical planning, design, and code reviews including peer code reviews • Provide Architecture and Technical Knowledge training and support for the solution groups • Develop good working relations with the other solution teams and groups, such as Engineering, Marketing, Product, Test, QA • Stay current with emerging trends, making recommendations as needed to help the organization innovate.

• Become a subject matter expert on traffic logs and analytics use cases across our customer segments • Develop hypotheses and execute rigorous research around customer problems and deliver robust root cause analysis • Use financial and engineering context to describe the total opportunity size (and business impact/ROI) of proposed product improvements; make synthesized recommendations on which customer problems to prioritize based on opportunity size • Lead product requirements, program milestones, and launch planning, particularly when it comes to transitioning customers off of old products and APIs in favor of modernized versions. • Document ideas and research quickly for review and iteration from your teams, to support our remote-first environment • Collaborate with adjacent product managers in the Channels Data team to connect and orchestrate data features across the domain.

• Develop, debug and support ETL processes utilizing AWS services • Lead ideation and development of data models used for data science and analytics • Meet the delivery expectations of the Agile Project Management methodology • Maintain and optimize reports and extracts that serve as lifesaving information sources to customers • Create clear and concise documentation regarding technical solutions, while sharing knowledge and documentation with teammates via “Lunch and Learns” • Collaborate with internal and external customers to deliver modern data products • Explore opportunities to enhance workflows through AI or automation tools (e.g., document summarization, task routing, or data parsing) • Identify repetitive tasks and partner with team leads to implement scalable automation solutions