Analytics Engineer, Mid-Level – CRM

• Design and build CRM data solutions by structuring datasets, tables, rules, and pipelines for campaigns, customer journeys, and relationship strategies
• Develop customer segmentation and intelligence at scale, transforming business needs into automated, reusable, and production-ready solutions
• Evolve the CRM data architecture, contributing to data modeling, integration, performance, quality, observability, and governance
• Develop and deploy data products and services consumed by CRM and other teams
• Build solutions using SQL, Python, and Databricks, with a focus on automation, efficiency, scalability, and reducing manual processes
• Apply AI Engineering and GenAI to develop automations, agents, tools, and solutions that provide access to data, insights, and knowledge
• Create mechanisms to democratize data and knowledge, reducing reliance on manual analysis
• Collaborate with stakeholders to translate business problems into technical requirements, data solutions, and measurable hypotheses
• Develop proofs of value, experiments, and measurement mechanisms to assess impact and support data-driven decision-making
• Ensure documentation, version control, testing, monitoring, and maintenance of solutions
• Own deliverables end to end, including estimation, planning, scope and timeline negotiation, risk identification, and progress reporting

• Advanced SQL, including the manipulation and transformation of large volumes of data
• Experience developing and operationalizing data solutions with Databricks
• Python applied to engineering, automation, data processing, and analysis
• Knowledge of data engineering, including pipelines, ETL/ELT, data modeling, integration, and data quality
• Knowledge of AI Engineering/GenAI, including building and integrating LLM-based solutions, automations, and agents
• Ability to develop solutions with production readiness, scalability, reliability, and reusability in mind
• Strong ability to connect technical decisions to business objectives and outcomes
• Clear communication skills and the ability to work effectively with both technical and business stakeholders
• Autonomy, organization, estimation skills, and the ability to manage your own deliverables
• Preferred qualifications: experience with CRM, Customer Analytics, customer segmentation and activation, experimentation/A-B testing, APIs, Git/CI/CD, Lakehouse architecture, Delta Lake, MLflow, and developing AI solutions integrated into corporate environments

• Employees can work remotely
• Equal opportunity and affirmative action employer
• People-centered, inclusive, and purpose-driven culture
• Professional development and investment in people and advanced technologies