Workstate is hiring a Senior Backend Developer! In this pivotal role, you will be responsible for building, optimizing and maintaining data pipelines using distributed computing on Cloud. The ideal candidate is an experienced data wrangler who can understand and optimize data systems from the ground up. The Data Engineer will support software developers, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture that is consistent throughout ongoing projects. You must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. Residents of Colombia or Argentina with the right to work in that country are eligible for this role. Responsibilities - Develop and operationalize scalable and reliable data pipelines. - Assemble large, complex data sets that meet functional and non-functional business requirements. - Experience in database management techniques including logical data modeling, physical database optimization and security. - Keep improving the integrity of data pipelines by setting up Data Quality checks to provide a comprehensive data service. - Work with Data and Analytics experts to strive for greater functionality in our data systems. - Experience with On-Call support and unblock users based on severity of the issue.

Workstate is hiring a Senior Backend Developer! In this pivotal role, you will be responsible for building, optimizing and maintaining data pipelines using distributed computing on Cloud. The ideal candidate is an experienced data wrangler who can understand and optimize data systems from the ground up. The Data Engineer will support software developers, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture that is consistent throughout ongoing projects. You must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. Residents of Colombia or Argentina with the right to work in that country are eligible for this role. Responsibilities - Develop and operationalize scalable and reliable data pipelines. - Assemble large, complex data sets that meet functional and non-functional business requirements. - Experience in database management techniques including logical data modeling, physical database optimization and security. - Keep improving the integrity of data pipelines by setting up Data Quality checks to provide a comprehensive data service. - Work with Data and Analytics experts to strive for greater functionality in our data systems. - Experience with On-Call support and unblock users based on severity of the issue.

Role Description 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. Qualifications - Bachelor’s degree in Computer Science, Engineering, Data Science, or related STEM field preferred. Equivalent practical experience will be considered. - 8+ years in data engineering, with 3+ years 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. Benefits - Comprehensive compensation. - Work-life balance initiatives. - Autonomy – we embrace personal freedom and responsibility. - Creativity – we are open to new ideas of how we can be better. - Growth – we want you to develop personally as well as professionally. - Top-notch professionals who are passionate about what they do. - People-oriented environment and supportive atmosphere. Company Description Rush Street Interactive (NYSE: RSI) is a market leader in online casino and sports betting, currently operating real-money gaming with our brands: BetRivers.com, PlaySugarHouse.com, and RushBet.co. We’re building bridges between online, social and land-based gaming businesses to create amazing, integrated experiences that keep players in the game. Rush Street Interactive is an equal opportunity employer and committed to a diverse and inclusive workplace. All qualified applicants will be considered for employment without regard to race, national origin, ancestry, sex, sexual orientation, sexual identity and expression, marital status, family status, lifestyle, age, culture, religion, military and veteran status, citizenship, or disability. Be at the forefront of this ground-breaking industry! Apply now!

• You will develop and maintain data models and structures that enable efficient querying and analysis; • You will design, develop, and maintain data pipelines to transform and process large volumes of data from various sources, while adding business context and semantics to the data; • You will implement automated data quality checks to guarantee data quality and consistency across the whole data life cycle..