Jobs at Kobie Marketing

The Senior Director, Client Services will lead client partnerships, ensuring alignment of loyalty strategies with enterprise goals, drive growth, and manage cross-functional collaboration.

Lead the observability strategy, manage the observability platform, drive automation, and ensure system reliability across production environments.

Design, optimize, and maintain database solutions for high-volume loyalty platforms. Build ETL/import-export processes, support data migration and integration, tune queries and procedures for performance, troubleshoot data quality issues, and collaborate with developers, QA, DBAs, and stakeholders in a DevOps environment.

As Director of Product, you will define and drive Kobie's data platform strategy to enhance marketing and loyalty programs, focus on AI integration, and develop commercial models.

The Decision Science Analyst role focuses on delivering actionable customer insights using loyalty data, collaborating with client teams to enhance sales and marketing strategies through data analysis and visualization.

Execute full-cycle, high-volume recruitment for Kobies remote Contact Center: source, screen, interview, extend offers, coordinate onboarding, maintain ATS integrity and talent pipelines, report recruiting metrics, partner with hiring managers, and improve recruiting processes and employer branding.

Lead and evolve financial-services loyalty programs through strategy, data-driven insights, cross-functional collaboration, campaign execution, performance monitoring, budget oversight, and client relationship management to maximize engagement and ROI.

The Director of Client Services will lead client relationships and oversee loyalty program delivery, ensuring alignment with client objectives. Responsibilities include strategic leadership, managing client accounts, driving growth, and mentoring team members.

As a Senior Account Manager, you will oversee client relationships, deliver insights, manage planning cycles, and coordinate program strategies to optimize loyalty programs.

The Director of Data Engineering will lead the design and delivery of enterprise data platforms, manage cross-functional teams, ensure data governance and perform program management to drive data-driven decision-making across the enterprise.

As a Sr. Software Engineer, you will improve existing code, solve performance issues, mentor team members, and develop web applications using Java and Spring.

As a Senior Software Engineer at Kobie, you will improve existing Java/Angular code, solve performance issues, develop cloud applications, and mentor team members while enhancing coding practices within an Agile environment.

Lead the design and operation of scalable, secure cloud platforms, mentor engineering teams, and ensure operational excellence while translating business requirements into technical solutions.

As a Senior Software Engineer, you will design and develop applications using Java and Spring, participate in Agile processes, and mentor team members while collaborating on innovative solutions.

As a Senior Data Engineer, you will design and implement scalable ETL/ELT frameworks, lead data engineering projects, and mentor a team while ensuring operational stability of data pipelines.

As a Data Engineer, you will implement ETL/ELT processes, develop data pipelines, and support data integrations to optimize loyalty insights.

As a Senior SDET, you will ensure system reliability through automation testing, analyze metrics, collaborate with teams, and drive QA processes.

As a Lead DevOps Engineer, you will build cloud infrastructure, own CI/CD pipelines, enhance observability, and lead incident response while collaborating with various engineering and AI teams.

The Lead Cloud Engineer will design, implement, and maintain infrastructure and deployment pipelines, mentor engineers, and drive automation best practices.

Lead design, operation, and reliability of production data pipelines in a multi-terabyte Snowflake environment. Translate client requirements into dimensional models, debug and remediate pipeline failures, evolve the data mart for event-driven and AI workflows, and improve pipeline trustworthiness via testing, CI/CD, audit logging, and documentation.