Data Platform Engineer Manager

Purple Wave is seeking an experienced and motivated Data Platform Engineer Manager to lead and mentor a team of platform engineers while driving the development and optimization of the data platform, backend services, and AI/ML capabilities the rest of the company builds on.

This remote-work eligible position requires both deep technical expertise and strong leadership abilities to ensure the successful execution of data platform initiatives -- spanning data pipelines, microservices and APIs, and the next generation of features powered by large language models (LLMs) and machine learning -- in support of business intelligence, analytics, and product decision-making.

The Data Platform Engineer Manager will oversee the design, development, and operation of the data platform and the backend services around it -- including ETL/ELT and dbt pipelines, workflow orchestration, data-quality and observability practices, and the Python microservices and APIs that serve data and integrate LLM and ML capabilities into production.

This role blends people leadership with technical direction: working closely with cross-functional teams, ensuring data integrity and reliability, optimizing platform processes and cost, and mentoring team members.

The ideal candidate will have a deep understanding of data platform and backend engineering principles and proven experience managing a team of technical professionals.

Responsibilities: Leadership: Lead and manage a team of data platform engineers, fostering a culture of innovation, collaboration, and continuous improvement through clear strategy, priorities, and feedback.

Collaborate: Partner with platform engineers, product teams, stakeholders, and other data teams to shape technical direction and refine data and service designs.

Team Building: Oversee hiring, onboarding, training, and development initiatives within the data platform team.

Data Quality & Governance: Establish and enforce data quality, reliability, and observability practices across pipelines (monitoring, lineage, freshness, and validation), ensuring consistency and security.

Backend & AI/ML Services: Oversee the design and operation of Python microservices and APIs, including those that integrate LLMs and ML models (RAG, embeddings, prompt orchestration, tool/function calling, and agentic workflows), and establish patterns for running LLM/ML-backed features safely, reliably, and cost-effectively in production.

Data Pipelines & Platform: Oversee the design, development, and maintenance of efficient, scalable data pipelines and ETL/ELT and dbt workflows across source systems, the warehouse, and downstream consumers.

Define and prioritize data platform projects, aligning with business goals and analytics needs.

Provide technical guidance, architectural review, mentorship, and career development support for the team.

Ensure best practices are followed in data engineering, backend development, security, and governance, including CI/CD, deployment automati...