Data Platform Engineering Manager

Purple Wave is seeking an experienced and motivated Data Platform Engineering 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 Engineering 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 automation, schema versioning/migration, and technical documentation.
• Conduct regular performance reviews and provide feedback to team members.
• Ensure seamless integration of data from various sources (CRM, marketing, operational systems) into the centralized data warehouse and downstream services.
• Optimize and enhance data infrastructure and pipelines for improved performance, reliability, and cost-efficiency.
• Review and optimize SQL queries, data models, and service/API performance to ensure efficient and reliable data delivery.
• Champion self-service tools and APIs that enable product teams to independently leverage backend and AI capabilities.
• Help form and oversee data governance and standardization initiatives within the data platform context.
• Partner with IT, product, and analytics teams to drive data-driven decision-making across the organization.
• Stay updated with emerging trends and technologies in data platform engineering, backend systems, and AI/ML to drive innovation.
• Undertake additional assigned duties as requested.
  
  

Supervisory Responsibilities:

• The Data Platform Engineering team directly reports to the Data Platform Engineer Manager.
• Responsible for hiring, onboarding, performance management, coaching, and career development of direct reports.
  
  

Qualifications:

• Bachelor’s degree in Computer Science, Data/Software Engineering, or a related field (or equivalent experience).
• 6+ years of technical experience in data platform, data, or backend engineering, including SQL, data pipelines, and ETL/ELT processes.
• Expertise in relational databases (MySQL, PostgreSQL), SQL performance optimization, and data warehousing solutions; familiarity with Redis and vector databases (e.g., pgvector, Pinecone, Weaviate) is a plus.
• Proficiency in Python; familiarity with Go and/or TypeScript/JavaScript is a plus.
• Proven experience building and scaling backend services and RESTful APIs, and leading teams that do the same; strong understanding of microservice architecture and distributed systems.
• Practical experience integrating LLMs or ML models into production systems — including several of: prompt engineering, RAG, embeddings/vector search, tool/function calling, evaluation, and cost/latency optimization.

• Strong understanding of data modeling, data integration, governance, and observability best practices (monitoring, logging, tracing), including for AI/ML workloads where applicable.

• Advanced experience with CI/CD pipeline design and hands-on experience with cloud-based data technologies (AWS, Azure, GCP, or similar); container orchestration (Kubernetes) is a plus.
• Experience with Tableau, Sigma, or other data visualization/BI tools is a plus.
• Excellent problem-solving skills with a passion for leveraging data to drive business outcomes.
• Ability to work collaboratively in a fast-paced environment, balancing multiple priorities.

• Spanish speaking bi-lingual candidates are encouraged to apply.

• Candidates may be requested to complete position specific skills assessments.
• Applicants must be either a U.S. Citizen or eligible to work in the U.S.
• Requires the ability to satisfactorily complete a background check.
  
  

Working Settings:

• Full-time Salaried Exempt, not eligible for overtime.
• Office hours are 8am-5pm, Monday through Friday, Central Time zone, additional hours may be required depending on priorities.

• This position is remote work eligible within the United States. Please be aware: the first week of employment includes mandatory in-person training. Remote start arrangements are not available.

• Also mandatory: One week a year of in-person training with the department.
• Potential for 10% travel, should the need arise.
• Prolonged periods sitting at a desk and working on a computer.
• Must be able to lift up to 15 pounds at times.
  
  

Compensation:

• The salary varies based on experience and qualifications, but typically ranges from $133,700 to $176,300 per year. Salary paid bi-weekly.
• Monthly Bonus Program - determined by the Company’s monthly revenue result and are paid on a “percent to plan” payout formula. (90% = $300, 100% = $600, 110% = $900, 120% = $1,200).
• Monthly phone stipend in accordance with the Company’s cell phone policy, currently $120/month.
• Health insurance, Dental insurance, and Vision insurance.
• 401(k) plan with an employer match up to 4% starting the first day of employment.
• Company-paid Life Insurance with options for supplemental coverage.
• Fully paid Short-Term Disability provided by the Company.
• 3 Weeks of PTO annually (details shared during onboarding).

• Employee Stock Purchase Program (ESPP) - Eligible to purchase company stock at a discount after 90 days of employment, with enrollment opportunities each May and November.