Global restaurant brands run their operation on the Crunchtime platform. Delivering a consistent guest experience across every location and managing food and labor costs are at the core of how Crunchtime’s software is used today in over 150,000 locations across 100+ countries by the world’s top restaurant and foodservice operators. Customers including Chipotle, Culver’s, Domino’s, Dunkin’, Five Guys and P.F. Chang’s rely on our top-ranked platform which now includes Zenput to manage inventory, staff scheduling, learning and development, food safety, operational tasks and audits. About the role Crunchtime is looking for a highly motivated Data Engineer to join our Connex product development team. The Connex team creates bi-directional real-time integration to every POS that our customers deploy. The ideal candidate is someone who enjoys integration, continual learning, and a fast-paced development environment. If you possess a drive for excellence, thrive in a fast-paced environment, and desire to be part of a team that is dedicated to being an industry leader, then we want to hear from you. What you’ll do as a Data Engineer - Own the planning, estimation, and delivery of data engineering tasks and projects, partnering with project management to track progress, milestones, and risks. - Design and implement scalable data pipeline solutions by analyzing customer data, identifying patterns, and performing data profiling to reverse engineer schemas and APIs. - Build, optimize, and maintain high-performance data pipelines, delivery networks, and bi-directional data integrations between customers and partners. - Ensure data reliability and quality through robust development of automated unit, integration, and regression tests. - Troubleshoot complex data and integration issues, providing escalated technical support and driving root cause resolution. - Collaborate cross-functionally to deliver integration solutions, and provide technical guidance, training, and documentation to internal teams and stakeholders. - Monitor data pipeline health, proactively identify performance or reliability issues, and implement improvements to ensure system stability. - Contribute to best practices in data engineering, including code quality, testing standards, and scalable architecture. What we’re looking for - 3+ years of professional experience in data engineering or software development with strong proficiency in SQL and Python. - Strong analytical and problem-solving skills with attention to detail and ability to work with complex datasets. - Experience designing and building scalable ETL/ELT pipelines, including working with APIs and handling structured and semi-structured data. - Solid understanding of data structures, algorithms, and data modeling concepts. - Experience with data validation, testing strategies (manual and automated), and ensuring data quality. - Strong communication and interpersonal skills, with the ability to work across teams and explain technical concepts clearly. - Ability to take ownership of tasks end-to-end, manage priorities, and deliver in a fast-paced environment. - Experience optimizing data pipelines for performance, scalability, and reliability. What you’ll get - Great mission-driven team members from diverse backgrounds with a strong company culture - Competitive pay - Unlimited PTO - Paid company holidays - Yearly team off-sites - International travel opportunities - Medical, dental, and vision benefits (FSA, HSA & HRA options) - Basic & Voluntary Life Insurance - 401k employer match - Wellness benefits (Headspace, OneMedical, Omada, Ginger.io, Gympass, Carrot) - Commuter benefits - Work in an open environment on solutions that are reshaping the way businesses operate - Fun team events - Ability to have a big impact - 10 weeks of paid parental leave - Fitness reimbursement - Learning & development funds Compensation: The annual base compensation range for this position is $75,000 - $105,000. The reasonably estimated total cash compensation (base + variable) range for this full-time position will be $80,625 - $112,875. Actual compensation is based on factors unique to each candidate, including, but not limited to: job-related skills, qualifications, education, experience, and location. Crunchtime has a location-based compensation system, so someone doing the same job in a different city might have a different pay range. Accessibility Accommodation Statement Crunchtime complies with federal and state disability laws and makes reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact recruiting@crunchtime.com. Equal Employment Opportunity Statement At Crunchtime, we are an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic. We have an inclusive and diverse workplace where every team member is respected and valued. As a global software development company, we believe that our diverse employee population enriches our work environment. Join us in our mission to provide the best software solutions to the food industry. We encourage you to apply regardless of your background or experience; even if you don’t meet all the qualifications, because we believe unique experiences and perspectives make us a stronger team.

Overview At Cotiviti, we are custodians of data for our clients. Using their technical experience in ETL processes, Data Engineers ensure operational functions are occurring as expected. This includes but is not limited to managing data implementations, data integrations, data production, data quality, and data security. Responsibilities - Create, maintain and execute intermediate to advanced Spark scripts for data management and data validation, and data integration. - Create, maintain and execute basic to intermediate SQL scripts for data management and data validation. - Optimize the queries to improve the efficiency of daily tasks. - Perform data analysis and identify any issues. - Work with other groups such as Engineering team, DBA, Cloud ops, etc. to troubleshoot and resolve any environmental or network issues that impact your work. Extend your support to after – hours or weekends as needed. - Create and maintain data pipelines as needed. - Validates the tasks results to ensure that all the requirements are met. - Adhere to all the industry level and organization level compliance rules and regulations to maintain data integrity. - Complete individual productivity tracking. - Complete task assignments using department ticketing system within assigned deadline. - Achieve organizational and individual goals as identified in performance reviews and goal setting exercises. - Complete all special projects and other duties as assigned. - Must be able to perform duties with or without reasonable accommodation. This job description is intended to describe the general nature and level of work being performed and is not to be construed as an exhaustive list of responsibilities, duties and skills required. This job description does not constitute an employment agreement and is subject to change as the needs of Cotiviti and requirements of the job change. Qualifications - Bachelor’s degree in Computer Science, Information Technology or equivalent work experience. - 3+ years of working knowledge of big data technologies (Spark, S3, Kafka, Ray, Hadoop, etc.). - 2+ years of working knowledge of big data / cloud technologies (Databricks, AWS, Azure, Hadoop, Spark, Snowflake etc.). - 3+ years of working knowledge of cloud (AWS, Azure, GCP, OCI etc.). - 3+ years of working knowledge of RDBMS (Oracle, MS SQL, Vertica, etc.) and experience using SQL, PL/SQL or other data integration/ETL tools. - Any Databricks / AWS certifications is a big plus. - Familiarity with data pipeline orchestration tools (e.g., Airflow, Databricks Workflows). - 3+ years of data analysis. Preferably in the Healthcare industry of enrollment, medical claims and/or pharmacy claims. - Proficient in Microsoft Office Suite applications PowerPoint, Word, Excel and Outlook. - Flexible work schedule. - Experience with project management tools like JIRA. - Databricks and/or Snowflake environment familiarity a plus. Mental Requirements: - Strong analytical skills. - Excellent verbal, listening and written communication skills. - Ability to multitask and prioritize projects to meet scheduled deadlines and tight turnaround times. - Ability to work well independently or in a team environment. Working Conditions and Physical Requirements: - Remaining in a stationary position, often standing or sitting for prolonged periods. - Repeating motions that may include the wrists, hands, and/or fingers. - Must be able to provide a dedicated, secure work area. - Must be able to provide high-speed internet access / connectivity and office setup and maintenance. Base compensation ranges from $105,000 to $125,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. For information about our benefits package, please refer to our Careers page. Since this job will be based remotely, all interviews will be conducted virtually. Date of posting: Applications are assessed on a rolling basis. We anticipate that the application window will close on 07//2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected. #LI-REMOTE #LI-LL1 #SENIOR

• Secure data sources, design data models, and build distributed components, pipelines, and tools that enable the organization to make analytical, data-driven decisions. • Develop and automate large scale, high-performance data processing systems (batch and streaming). • Build scalable data pipelines leveraging orchestration technologies. • Design our data models for optimal storage and retrieval to meet critical product and business requirements. • Understand and influence logging to support our data flow, architecting logging best practices where needed. • Contribute to shared Data Engineering tooling & standards to improve productivity and quality of output for Data Engineers across the company. • Improve data quality by using & improving internal tools to automatically detect issues. • Design and implement data pipelines and data summarization processes using SQL and apply understanding of relational data structures. • Create a summary data platform supporting our presentation layer that allows clinicians and operators to pinpoint interventions on-demand to patients most in need. • Locate trends in data sets and build algorithms for large and complex data sets. • Analyze and design the best ways to expand our data model to incorporate mission critical data. • Analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions. • Own projects to design and implement best-in-class data processing enabling clean data flow directly to employer’s data model and on to our presentation layer. • Assist with development of systems, strategies, and standards to ensure the quality of data collected, organize and maintain the data properly, and effectively deliver data needed by primary care physicians to manage patient healthcare. • Work with analytics, engineering, and operations to design and implement new analytics products that support improving patient health. • Follow data best practices, including engagement in project status meetings and self-education on new technologies and practices. • Design a new concept within our data model to meet a new operational or analytical need.

• Develop and automate large scale, high-performance data processing systems (batch and/or streaming) to drive business growth • Build scalable data pipelines leveraging orchestration technologies allowing for easy monitoring and troubleshooting • Design data models for optimal storage and retrieval • Improve data quality by using and improving internal tools to automatically detect issues • Create a summary data platform supporting presentation layer • Work with analytics, engineering, and operations to design and implement new analytics products