Staff Data Engineer

As a Staff Data Engineer, you'll partner closely with Data Services, Analytics Engineering, Product, and Business stakeholders to design and deliver scalable, reliable, and high-quality data solutions. You will play a key technical leadership role, helping shape the architecture, standards, and future direction of our data platform. The ideal candidate combines deep technical expertise with strong communication skills, a passion for data, and an interest in sports, gaming, and digital products.

About the Work

As a key member of our team, you will:

• Collaborate with business stakeholders to identify and prioritize data-driven opportunities and initiatives.
• Design, build, and maintain scalable data pipelines supporting analytics, reporting, product, and operational use cases.
• Develop, test, and optimize dbt models following data modeling best practices.
• Manage and support orchestration platforms including Airflow and exposure to Dagster.
• Design and implement dimensional, semantic, and analytical data models to support self-service analytics and business intelligence.
• Drive data architecture decisions and establish engineering standards and best practices across the organization.
• Partner with data engineers and platform teams to improve the reliability, scalability, and performance of our data ecosystem.
• Develop and maintain data quality frameworks, testing strategies, and observability solutions to ensure trusted data assets.
• Support governance initiatives through documentation, metadata management, lineage, and data ownership practices.
• Complete complex analyses and provide actionable recommendations to business stakeholders.
• Oversee team analysis to ensure data accuracy, consistency, and business relevance.
• Champion adoption of data exploration and self-service analytics tools across the organization.
• Lead technical design reviews and provide mentorship through code reviews, architectural guidance, and knowledge sharing.
• Support data engineer hiring, onboarding, mentoring, and continued professional development.
• Participate in incident response, root cause analysis, and continuous improvement initiatives for critical data platform issues.
• Other duties as required.

About You

• Bachelor's degree in Computer Science, Data Engineering, Statistics, Information Systems, Business, or a related field.
• 8+ years of experience in data engineering, analytics engineering, or a related discipline.
• Hands-on expertise with BigQuery, dbt, Airflow, Python, SQL, and modern cloud data platforms.
• Strong understanding of data warehousing concepts, ETL/ELT design patterns, and dimensional modeling.
• Experience building and optimizing scalable data transformation pipelines in cloud environments.
• Experience working with Google Cloud Platform services such as BigQuery, Cloud Storage, Pub/Sub, and Cloud Composer.
• Exposure to Azure data platforms and services is a plus.
• Proficiency with Git-based development workflows, CI/CD pipelines, and software engineering best practices.
• Experience implementing automated testing, monitoring, and data observability solutions.
• Experience with data visualization and exploration tools such as Looker, Mode, Tableau, or similar platforms.
• Excellent communication and stakeholder management skills, with the ability to translate business requirements into scalable technical solutions.
• Proven ability to lead complex projects and influence technical direction across multiple teams.