Sr. Data Engineer

The Opportunity:   

As a Senior Data Engineer at Vivid Seats, you’ll have the opportunity to shape how millions of fans experience live events. You’ll take ownership of designing and building high-impact data solutions that power everything from real-time ticket transactions to advanced analytics that guide business decisions. 

 In this role, you’ll drive innovation by creating scalable data pipelines and integration flows that directly influence product features and customer experiences. You’ll work hands-on with modern cloud technologies in AWS and explore emerging tools in AI, ML, and LLMs - giving you the space to expand your technical expertise while solving meaningful problems that shape seamless, end-to-end customer experiences, from browsing events to receiving tickets at the box office. 

How your role contributes to the success of Vivid Seats:   

• Design and build scalable data systems and automated processes that power our cloud infrastructure and deployment pipelines. 

• Collaborate across engineering teams to deliver scalable data integrations and transformation pipelines while shaping the underlying data architecture for transactional and analytical use cases. 

• Enable AI and ML initiatives by designing and maintaining data pipelines and architectures that support predictive models and automation in Marketing, Pricing, and Customer Service. 

• Elevate platform stability by driving best practices, automation, and monitoring across the data ecosystem. 

• Stay ahead of emerging technologies and integrate valuable concepts to continuously enhance our data architecture and capabilities. 

• Mentor and support teammates, helping them stay unblocked, productive, and challenged to grow. 

• Champion engineering best practices, fostering a culture of quality, collaboration, and continuous improvement. 

• Collaborate with leadership and cross-functional partners to set realistic delivery expectations, navigate trade-offs, and solve complex technical challenges. 

How your role expectations will progress as a Senior Data Engineer in the first 30, 90, and 180 days:   

 30 days in   

• Complete new hire onboarding and gain the resources needed to be effective in your role. 

• Develop a strong understanding of how ticket marketplaces operate and identify where your contributions will improve the customer experience. 

• Acclimate to team and company norms, business objectives, and Vivid Seats’ values. 

• Build foundational knowledge of the applications, tech stack, and development processes. 

• Begin delivering high-impact work by contributing to the design, development, and deployment of data solutions that support business and analytics needs. 

90 days in   

• Enhance processes, methods, and technologies to mitigate risks, improve efficiency, and elevate the overall data platform. 

• Build and leverage relationships across teams to drive initiatives forward and achieve organizational goals. 

• Apply technical expertise to contribute to the product and technology roadmap, aligning your work with company-wide objectives. 

• Participate in goal planning and infrastructure design sessions, providing guidance and insight based on your experience. 

• Deliver high-quality data solutions and provide thoughtful code/review feedback that strengthens team capabilities. 

• Identify core data challenges and propose solutions, technologies, or improvements that address organizational needs. 

• Begin supporting AI/ML initiatives, contributing to Python-based data workflows and assisting with data preparation for predictive modeling or analytics projects. 

180 days in   

• Take full ownership of major data initiatives, designing and implementing robust, scalable solutions that advance key business objectives. 

• Lead process improvements that increase efficiency, reliability, and quality across the data ecosystem. 

• Mentor and coach teammates, actively fostering technical growth and knowledge sharing across the team. 

• Guide and influence team priorities to ensure alignment with broader engineering and organizational goals. 

• Identify opportunities to optimize core systems, data workflows, and platform performance, contributing measurable improvements to the overall data infrastructure. 

• Champion best practices in data engineering, code quality, and system monitoring, setting the standard for technical excellence within the team. 

• Contribute to AI/ML and data science initiatives, leveraging Python and libraries such as Pandas, NumPy, and Scikit-learn, as well as AWS SageMaker, with guidance from data science collaborators. 

What You’ll Bring:   

• 7+ years of professional experience in data engineering, analytics, or data Science development, with a proven track record of designing and delivering large-scale data systems. 

• Deep expertise in cloud-based relational databases, such as Aurora RDS(MySQL), for transactional systems. 

• Experience with cloud-based analytical databases, such as Snowflake, BigQuery, or Redshift, for advanced analytics. Familiarity with Snowflake Intelligence, Cortex AI, or AI/ML integrations is a plus. 

• Hands-on experience with ETL pipelines, workflow orchestration (e.g., Airflow), and scripting using Python, Java, or Bash. 

• Experience with AI/ML workflows using Python and libraries such as Pandas, NumPy, and Scikit-learn, particularly with AWS SageMaker. Familiarity with data science concepts is a plus. 

• Experience conducting vendor evaluations and assessing emerging technologies, such as vector databases and in-memory document/object databases, to guide strategic adoption. 

• Collaborative mindset with a passion for mentoring and helping teammates grow, while effectively communicating across technical and business stakeholders. 

Vivid Seats Pay Transparency Disclaimer: Full time offers from Vivid Seats include annual bonus incentives and equity for all employees; FLEX PTO; mental health days; medical, dental, and vision insurance; 401K matching; monthly credits and discounts for attending live events; and a variety of additional workplace perks. The typical starting salary within the full salary range for this position can range. Factors which may affect starting salary include geographic market, relevant skills/experience, education, and other qualifications.