Role Description The Survey Manager is a member of the Survey Team within the SullivanCotter Business Unit and is responsible for leading all phases of the survey and reporting process. This role cultivates and maintains strong relationships with both internal stakeholders and external clients to ensure the delivery of high-quality survey products and reporting. - Collaborates closely with consulting partners and other Survey Managers to support the report delivery process. - Works cross-functionally with external clients, functional IT teams, internal consultants across practices, and software delivery team members. - Supports the report delivery process and ensures efficient execution and successful product delivery. - Establishes clear expectations and effective collaboration between the Survey Team and other SullivanCotter teams. Qualifications - Bachelor of Science or Bachelor of Business Administration, computer science, data analytics/statistics or equivalent degree. - 7+ years of relevant experience in data analytics, statistical research or product management. - Solid technical knowledge and experience working with Excel, Word, PowerPoint, and SmartSheet. - Demonstrates ownership of assigned tasks and dedication to get the job done. - Flexible, adaptable, and able to work under tight deadlines or changing needs. - Exceptional client service orientation. - Diligence. Requirements - Leads the end-to-end survey lifecycle, serving as project manager across all phases including survey build, launch, close, and reporting. - Oversees questionnaire development, data collection, cleaning, analysis, and reporting. - Manages report production, including layout, table and graph generation, narrative development, proofing, and editing. - Ensures consistency in analytical approaches, interpretation of findings, and development of insights and recommendations. - Oversees quality assurance practices to ensure the accuracy, completeness, and integrity of survey data and reporting outputs. - Builds and maintains strong working relationships with consulting partners, clients, and survey team members. - Identifies and implements opportunities to improve survey products, processes, and operational efficiency. - Utilizes the Databricks workspace to run queries, review SQL notebooks, and leverage Databricks AI Assistant. Benefits - Competitive total compensation package. - Medical and dental coverage at no premium cost for employees. - 401(k) and profit-sharing retirement plans. - Flexible spending accounts. - Paid time off (PTO). - Company-paid holidays. - Gender-neutral parental leave. - Bereavement and pet leave. - Continuing education and professional accreditation sponsorship. - Life and AD&D insurance. - Short- and long-term disability. - Employee assistance program. - Mental health support program.

Role Description This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Data Engineer - REMOTE. You will play a crucial role in shaping the backbone of the data platform, ensuring security, reliability, and trust while managing vast volumes of data from workouts and health-related sources. Your expertise will directly impact product innovation, AI, and analytics, allowing our partner to continue redefining the training experience. By building and scaling data systems, you'll contribute to personalizing experiences and enhancing coaching. Your work will ensure that sensitive information is protected while maintaining compliance with an ever-evolving regulatory landscape. - Architect secure and scalable data systems that support growth and meet regulatory standards. - Build and optimize data models and pipelines across diverse sources: sensors, workouts, and health integrations. - Establish controls for access, encryption, anonymization, monitoring, and auditability. - Define and enforce best practices for managing sensitive data, including PHI and PII. - Collaborate with teams across various departments to translate needs into compliant solutions. - Conduct risk assessments and implement safeguards guided by NIST frameworks. - Support SOC 2 audits by documenting and demonstrating effective security controls. - Mentor engineers and scientists, setting high standards for secure data engineering. - Continuously evolve the platform, introducing tools and frameworks to balance innovation with regulatory compliance. Qualifications - 8+ years of experience in data engineering, or 6+ years with a Master’s degree (or equivalent). - Strong skills in SQL, Python, and distributed data processing (Spark, Databricks, or similar). - Experience building pipelines with DBT, Airflow, Fivetran, or related tools. - Background in data modeling and warehousing with systems like Snowflake, Databricks, or Redshift. - Hands-on experience working with regulated environments and sensitive data. - Familiarity with frameworks such as HIPAA, SOC 2, and NIST for security and compliance. - Skilled in access control design, audit logging, encryption, and governance. - Excellent communicator who can explain complex tradeoffs to both technical and non-technical audiences. - Known for technical leadership and mentoring, raising the bar for engineering quality. Benefits - Flexible work schedule with remote opportunities. - Collaborative work environment with cross-functional teams. - Opportunities for professional growth and development. - Inclusive culture that celebrates diversity and nurtures unique perspectives. - Support for accessible work arrangements and accommodations. - Innovative projects that leverage cutting-edge technology and data. - Participation in ongoing training and skill enhancement programs.

• Respecting privacy and ensuring security while offering valuable insights • Making inquisitive choices in tech stack, database design, and encryption • Building analytical models for reporting to administrators • Helping school principals understand how education is delivered • Architecting data warehouse schemas and SQL transforms • Creating data solutions using tools like Snowflake, Airflow, DBT, SQL, Python, Cube.dev • Leading collaboration on cross-functional teams and participating in workshops

• Design and oversee the development of scalable generative AI systems and enterprise-grade AI platforms. • Establish robust architectures that support model training, inference, monitoring, and lifecycle management in production environments. • Direct the selection, customization, and enhancement of state-of-the-art generative AI and large language models. • Develop and execute APIs, microservices, and integration frameworks to incorporate AI capabilities into enterprise applications. • Ensure that AI platforms meet stringent standards for performance, reliability, security, and scalability, while also adhering to data governance and privacy regulations. • Collaborate closely with product, engineering, and business teams to outline technical requirements and approaches to AI architecture. • Architect end-to-end pipelines for deploying and monitoring AI models, ensuring seamless integration with existing systems. • Guide architectural decisions for LLM applications, AI workflows, and distributed AI infrastructure. • Institute best practices for ethical AI development, including strategies to mitigate risks like model hallucinations, bias, and reliability challenges. • Provide technical mentorship and guidance to engineering teams, while contributing to the formulation of long-term technology strategies and the advancement of AI platforms.