The Data Product Manager – Curation is responsible for designing and managing curated data products that power reporting, analytics, and emerging advanced analytics use cases across RSI like Machine Learning. This role focuses on building trusted, well-modeled, and well-documented data layers that translate raw source data into reusable, business-aligned datasets. 

The position partners closely with analytics and analyst teams as well as data and analytics engineering to improve data consistency, usability, and self-service adoption. While machine learning and advanced analytics are longer-term areas of evolution, this role lays the semantic and structural foundation required to support them in the future. This role is critical to closing the gap between ingestion and insight and strengthening RSI’s enterprise data maturity. 

What You'll Do:

• Design and manage curated data products composed of fact and dimension tables optimized for reporting, analytics, and downstream analytical use cases. 
• Develop and maintain semantic and subject-area data models that support analytics self-service and consistent business definitions. 
• Partner with analytics and BI teams to understand reporting needs and translate them into scalable, reusable curated datasets. 
• Lead schema design, join logic, and standardization efforts to improve trust, consistency, and cross-domain usability of data. 
• Collaborate with data engineering teams on data transformations, modeling standards, and performance optimization. 
• Support future advanced analytics and ML use cases by ensuring curated datasets are well-structured, well-documented, and extensible. 
• Establish governance standards for curated datasets, including documentation, lineage, naming conventions, and data quality monitoring. 
• Track adoption and usage of curated data products, incorporating stakeholder feedback to iteratively improve models and definitions. 

What You'll Bring:

• Bachelor’s degree in Information Systems, Data Science, Computer Science, or a related field, preferred, or equivalent experience. 
• 5+ years of experience in data product, analytics infrastructure, or data modeling roles. 
• Stakeholder Management: 5+ years of experience partnering with BI, analytics, and business stakeholders to gather requirements and deliver trusted data products. 
• Analytics & Product Thinking: Strong understanding of how curated data enables reporting, self-service analytics, and consistent decision-making. 
• Data Modeling: 3+ years of experience designing dimensional models, schemas, and semantic layers for analytics or reporting use cases. 
• ML Awareness (Foundational): General familiarity with how curated data may support future ML or advanced analytics use cases (e.g., feature readiness, aggregation strategies), without expectation of hands-on model development. 
• Technical Proficiency: Advanced SQL skills and hands-on experience working with data marts, transformations, and analytical datasets. 
• Documentation & Governance: Experience maintaining semantic definitions, data catalogs, and quality standards to ensure data is discoverable, explainable, and trustworthy. 
• Able to travel occasionally both domestically and internationally. #LI-REMOTE 

We are a mobile-first organization evolving our digital platform toward a modern, scalable, event-driven architecture. As a Sr. Front End Engineer, you will play a foundational role in building and evolving our client applications and the event orchestration architecture that powers them.

This role extends beyond traditional feature development. You will help architect and implement scalable client-side instrumentation frameworks, shared frontend capabilities, and integration patterns that enable structured event collection, analytics, lifecycle engagement, and downstream data systems.

You will work in close coordination with feature-delivery teams to ensure instrumentation and orchestration standards are embedded directly into product development. In parallel, you will help shape the long-term evolution of our client event architecture.

This position requires deep frontend and mobile expertise combined with systems thinking, architectural rigor, and a strong understanding of scalable event-driven systems.

What You'll Do:

Client & Mobile Engineering

• Frontend development across web and native mobile platforms (React, Angular, TypeScript, iOS, Android).
• Contribute to and evolve a modular, scalable micro-frontend architecture.
• Build reusable frontend components and shared client frameworks.
• Optimize performance and responsiveness across devices, with particular focus on mobile reliability and efficiency.
• Establish best practices for SDK integrations, consent enforcement, observability, and client performance.

Event Instrumentation & Orchestration

• Design and implement structured event instrumentation frameworks across web and mobile applications.
• Instrument native iOS and Android applications, including analytics/CDP SDK integration with attention to performance, batching, offline handling, and reliability.
• Define, version, and govern structured event schemas and taxonomy standards.
• Architect scalable integration patterns between client applications, backend services, and downstream data platforms.
• Ensure event data is reliable, well-structured, and suitable for streaming, analytics, identity resolution, and activation use cases.
• Support monitoring, debugging, and continuous improvement of client event pipelines.

Cross-Functional

• Partner closely with Product, Analytics, and Engineering teams to align instrumentation and architecture with business objectives.
• Participate in architectural discussions that shape long-term platform modernization.
• Balance ongoing support needs with forward-looking architectural improvements.
• Mentor engineers, conduct code reviews, and elevate frontend and mobile engineering standards.
• Clearly communicate technical concepts to both technical and non-technical stakeholders.

What You'll Bring:

• 8+ years of experience in software engineering with strong frontend expertise.
• Deep experience building and scaling web and native mobile applications.
• Strong proficiency in React, Angular, TypeScript, and native iOS/Android development.
• Proven experience implementing analytics or CDP SDKs within mobile applications.
• Strong understanding of event-driven architecture and structured event schema design.
• Experience integrating client event streams into CDPs and downstream analytics platforms.
• Familiarity with relational databases (Postgres, Oracle) and analytical platforms (e.g., Snowflake).
• Experience with CI/CD pipelines, Git-based workflows, and modern development tooling.
• Strong understanding of data integrity, governance, observability, and privacy best practices.
• Demonstrated ability to lead technical discussions and influence architectural decisions.
• Excellent written and verbal communication skills #LI-REMOTE #LI-PROMOTE

The Director of Data Engineering will lead and scale the Data Engineering and Analytics Engineering functions, owning the post-application data platform and its architecture, governance, and operating model. This foundational leadership role ensures best in class engineering standards, helps drive the organization toward a durable, auditable, data-product operating model, and modernizes and expands a Snowflake-centered data stack to include building and operating scalable distributed data processing and real-time streaming systems that support event-driven data products for operational use cases.

The role partners closely with Product, Software Engineering, Data Product Managers, Marketing, Compliance, Finance and Data Science to ensure our data ecosystem is production-grade, scalable, and compliant in a regulated gaming environment.

What You'll Do:

Team Leadership & Organizational Growth

• Lead and grow Data Engineering and Analytics Engineering teams; recruit, mentor, and elevate technical capabilities around distributed data processing, stream processing, and event-driven architectures
• Define ownership models for platform components and data products; set performance and hiring plans.
• Advance engineering standards for deployment: development, testing, documentation, release management, and SLAs.
• Partner with Data Product Managers to define data assets as versioned, documented data products with clear ownership and SLAs.

Platform, Architecture & Engineering Excellence

• Own the administration, reliability, governance, and strategic expansion of the Snowflake-based post-application data platform to operate scalable distributed data processing pipelines capable of handling high-volume event data across both batch and streaming workloads.
• Manage platform governance, access control, security, cost, and capacity planning.
• Standardize DBT deployment methods, promotion workflows, and environment management.
• Implement Infrastructure-as-Code (Terraform or similar) for reproducible, auditable infrastructure.
• Deliver monitoring, observability, lineage, and data quality frameworks; enforce traceability and auditability for regulated reporting.
• Own and evolve ingestion and warehouse architecture and transformation frameworks .
• Improve performance, cost efficiency, reliability, and scalability of data transformation and storage layers.
• Define and enforce engineering standards across the data lifecycle and establish SLAs and reliability metrics for critical assets - ensuring all pipelines, transformations, and reporting are auditable and documented for internal and external review

Event-Driven Architecture & Player 360

• Partner with Software Engineering on event messaging, streaming architecture, and ingestion patterns (built on technologies such as Kafka, Kinesis, Spark Structured Streaming, Flink, or equivalent platforms).
• Lead technical design and development of a unified Player 360 data foundation that integrates transactional, behavioral, and event-level data.
• Align application schema design with downstream analytical, product, and regulatory requirements.
• Balance real-time and batch processing strategies according to business needs and cost/complexity tradeoffs.

What You'll Bring:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related STEM field preferred. Equivalent practical experience will be considered.
• 8+ years of experience in data engineering, with 3+ years of experience in leadership roles. 
• Experience transitioning an organization from private/startup to public company.
• Experience in regulated industries (gaming, fintech, payments, healthcare).
• Prior experience building Player 360 / Customer 360 platforms.
• Deep hands-on experience with Terraform / IaC and production-grade streaming systems (Kafka, Kinesis, etc.).
• Familiarity with GenAI governance frameworks and scalable AI integration patterns such as Harness Engineering.
• Able to travel occasionally both domestically and internationally. #LI-REMOTE #LI-PROMOTE

The Analytics Engineering Technical Lead will define and own the modeling architecture, standards, and technical direction within RSI’s cloud-native Data Platform. This role is accountable for ensuring that analytics-ready data is reliable, scalable, and aligned to long-term business needs across growth, operations, and risk.

You will lead the design and governance of core data models in Snowflake and dbt, establishing best practices that enable high-quality, self-service analytics without sacrificing trust or performance. As a hands-on technical leader, you will set standards for modeling, testing, documentation, and deployment while mentoring other Analytics Engineers and raising the overall technical bar of the team.

This role partners closely with Data Engineering, Analytics, and business stakeholders to translate evolving requirements into durable data products. You will help balance speed and governance, prioritize platform investments, and ensure our data foundation scales with the business.

Our modern data stack includes Snowflake, AWS, Python, Airflow, and dbt.

What You'll Do:

• Lead the design, development, and lifecycle management of curated datasets, dbt models, and analytics data marts aligned to business domains and metrics.
• Establish and evolve standards and best practices for dbt modeling, testing, documentation, and code organization to support long-term scalability.
• Ensure analytical datasets are accurate, reliable, and trusted, serving as a single source of truth for business, product, and stakeholders.
• Embed data quality checks, documentation, and governance directly into analytics pipelines.
• Partner closely with Product, Data Engineering and Analytics teams to translate business requirements into well-modeled, performant data products.
• Mentor and support Analytics Engineers through technical guidance, design reviews, and knowledge sharing.
• Continuously improve and modernize analytics workflows by introducing automation, tooling enhancements, and AI-assisted development where appropriate.
• This role includes technical leadership and mentoring responsibilities for the team, including other Analytics Engineers.

What You'll Bring:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related quantitative discipline.
• Technical Leadership: Proven experience defining technical direction, standards, and architectural decisions within analytics engineering or curation teams.
• Data Modeling Expertise: Deep understanding of dbt, data marts, dimensional modeling, and self-service BI enablement.
• Data Engineering Background: 7+ years of experience in data warehousing or development; 5+ years of experience in hands-on data engineering using SQL and Python.
• Cloud Infrastructure: Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization (Docker/Kubernetes).
• Tooling & Orchestration: Experience with tools like dbt, Airflow, S3, REST APIs, and large-scale DWHs (Snowflake, Redshift, BigQuery, etc.).
• Change Management: Skilled at leading cross-functional data initiatives and driving adoption of new tools and standards.
• People Leadership: Experience mentoring and guiding distributed teams across time zones.
• Communication: Strong written and verbal English skills with the ability to collaborate across technical and business functions.
• Able to travel occasionally both domestically and internationally #LI-HYBRID