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# Data Platform Engineer Manager

- **Company:** Amazon.com, Inc.
- **Location:** Manhattan, KS, United States (Remote available)
- **Experience:** Expert
- **Salary:** $133,700.0 - $176,300.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Performance Management, Microsoft Azure, Cloud Database, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Visualization, Data Warehousing, Relational Databases, Distributed Systems, Python (Programming Language), PostgreSQL, Machine Learning, MySQL, Redis, Azure Machine Learning, Search Technologies, Software Engineering, SQL Databases, Tableau (Software), TypeScript, Management of Software Versions, Workflow Management Systems, Data Logging, Google Cloud, Large Language Models, Prompt Engineering, Backend, Kubernetes, Information Technology, Deployment Automation, Operational Systems, Data Delivery, Restful APIs, Data Pipelines, Sql Tuning, Microservices
- **Published:** September 29, 2026
- **Apply:** https://www.careerjet.com/job/us91d802ae08fe45659b87ae3d03324426/eaa

## About the Role

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

## Description

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 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


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