• Design, build, and operate data pipelines that process terabytes of transactional data daily using Airflow/Composer and BigQuery • Own end-to-end data models and transformations that power merchant analytics, operational reporting, and ML features • Build and maintain embedded analytics infrastructure — the data products our merchants interact with directly • Evolve our data platform on GCP, including BigQuery, Cloud SQL, AlloyDB, and CDC datastreams • Improve data quality and reliability through testing, observability, alerting, and validation frameworks • Own data lineage, metadata, and documentation, and help prepare our data layer for agentic and LLM-powered use cases with semantic clarity and standardized metric definitions • Collaborate cross-functionally with product, ML, and GTM teams, and contribute to technical direction through design docs and architecture decisions

Role Description As a Senior Data Engineer within our Direct-to-Consumer Sports & Entertainment division, you will play a critical role in designing and scaling the data systems that power insights across platforms like Fandango and Rotten Tomatoes. This role sits at the intersection of data architecture, engineering, and business impact—enabling teams to make faster, smarter decisions that shape how millions of fans discover and experience content. Why This Role Matters: - You will help transform complex data into reliable, scalable systems that drive analytics, reporting, and product innovation. - Your work will directly influence how we understand customer behavior, optimize experiences, and unlock new opportunities across our digital ecosystem. - This is a remote-first role, with opportunities for intentional in-person collaboration (approximately 10%) to support team connection, planning, and innovation. - You will also participate in an on-call rotation supporting production systems. What You'll Do: - Design and build scalable data pipelines, data marts, and warehouse solutions to support analytics and reporting. - Develop and optimize SQL-based data models, schemas, and queries for performance and reliability. - Build and maintain ETL/ELT processes using tools such as Airflow, AWS Glue, and cloud-native services. - Partner with cross-functional stakeholders to translate business needs into technical data solutions. - Troubleshoot and resolve data issues in production environments, ensuring data quality and availability. - Mentor and support other Data Engineers while contributing to best practices and architectural decisions. Qualifications - 7+ years of experience in data warehousing, OLAP systems, and dimensional data modeling. - Strong expertise in SQL (T-SQL or PostgreSQL) and experience with performance tuning and indexing. - Proficiency in Python and experience building data pipelines in modern orchestration tools (e.g., Airflow, AWS Glue). - Hands-on experience with cloud platforms such as AWS, Azure, or GCP and data warehouses like Redshift. - Experience working with APIs, NoSQL databases, and distributed data systems. - Ability to collaborate with technical and non-technical stakeholders to solve complex business problems. Requirements - Trust & Integrity: You build reliable, high-quality data systems and take ownership of outcomes. - Teamwork: You collaborate effectively across engineering, product, and business teams. - Transparency: You communicate clearly on progress, challenges, and solutions. - Agility: You adapt quickly in a fast-paced environment and continuously improve systems and processes. - Entrepreneurial Spirit: You proactively identify opportunities, innovate on solutions, and drive impact. Benefits - Be part of a transformative media company shaping the future of sports and entertainment experiences. - Work on products that reach tens of millions of users globally. - Remote-first flexibility with intentional in-person collaboration opportunities. - Competitive compensation and comprehensive benefits package. - Opportunities for growth, learning, and career advancement within a dynamic and evolving organization. Company Description VERSANT is a leading force in news, sports and entertainment - home to iconic and trusted brands that inspire, inform, and delight audiences. Our unique combination of content, technology and services enriches the cultural fabric, igniting passions, sparking conversations, and connecting people to what they love most. As an independent, publicly traded company, VERSANT brings together powerhouse cable networks - including USA Network, CNBC, MS NOW (formerly MSNBC), Oxygen, E!, SYFY, and Golf Channel - with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine. Together, these businesses reflect our commitment to delivering exceptional experiences across every screen and service. VERSANT is an industry-changing media company fueled by innovation and an entrepreneurial spirit. With a strong foundation and a forward-looking vision, VERSANT empowers creativity, embraces change, and drives connection in an ever-evolving world.

• Monitor and optimize data pipelines, workflows, and automated routines in a production environment; • Analyze logs, metrics, and events for root cause investigations, applying advanced analysis techniques and, when possible, predictive models; • Develop and enhance automation mechanisms for error remediation, reprocessing, and pipeline recovery; • Implement continuous improvements to pipelines with a focus on efficiency, scalability, and reliability; • Support Machine Learning and AI initiatives, including data preparation, model monitoring, and maintaining inference pipelines; • Document technical procedures, incidents, and automated playbooks.

• Analyze user behavior, product performance, and key business metrics to identify trends and opportunities. • Create and maintain interactive dashboards and reports using tools like Tableau, Looker, Power BI, or Google Data Studio. • Collect, clean, and structure large datasets to ensure accuracy and usability. • Define and track KPIs for marketing, product, and business performance. • Work with SQL, Python, or R to extract, analyze, and manipulate data. • Collaborate with product managers, engineers, and marketing teams to provide data-driven insights. • Conduct A/B testing and experiment analysis to improve product features and user engagement. • Identify bottlenecks and opportunities in user journeys and customer funnels. • Present findings in a clear and compelling way to stakeholders and leadership teams. • Stay up to date with industry trends, analytics best practices, and emerging data tools.