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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer, AI Platform - **Company:** PROPERTY VALUE, INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $134,000.0 - $168,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Apache HTTP Server, Software Applications, Automated Storage and Retrieval Systems, Microsoft Azure, BigQuery, Continuous Integration, Data Architecture, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Dimensional Modeling, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Metadata, Meta-Data Management, Cloud Services, Search Technologies, Data Streaming, Unstructured Data, Google Cloud, Sql Optimization, System Availability, Large Language Models, Snowflake, Apache Spark, Generative AI, Data Layers, Event Driven Architecture, Microsoft Fabric, Data Lakes, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Real Time Data, Apache Kafka, Data Management, Machine Learning Operations, Virtual Agents, Data Pipelines, Amazon Redshift, Databricks - **Published:** August 23, 2026 - **Apply:** https://www.dice.com/job-detail/6958619d-7818-4a75-8827-f08e6b370ca6 ## About the Role * 8+ years of experience designing, building, and operating enterprise-scale data platforms. * Deep expertise with modern cloud data platforms such as Snowflake, Databricks, Microsoft Fabric, BigQuery, Redshift, or similar technologies. * Advanced SQL and Python skills with strong experience in data modeling, ELT/ETL development, dbt, and orchestration frameworks such as Airflow, Dagster, or equivalent. * Experience building scalable streaming and event-driven architectures using technologies such as Kafka, Azure Event Hubs, Spark, or similar platforms. * Strong understanding of modern data architecture patterns, including dimensional modeling, semantic layers, data governance, metadata management, and platform observability. * Experience supporting AI and machine learning workloads through AI-ready data models, vector search, metadata enrichment, Retrieval-Augmented Generation (RAG), and knowledge retrieval systems. * Experience with modern lakehouse technologies and open table formats such as Apache Iceberg, Delta Lake, or similar technologies. * Hands-on experience with cloud platforms (Azure preferred; AWS or Google Cloud Platform also acceptable). * Strong engineering mindset with experience in testing, CI/CD, infrastructure automation, and operational excellence. * Proven ability to lead technical initiatives, mentor engineers, and collaborate effectively across technical and business teams. * Strong sense of ownership and accountability for data accuracy, consistency, reliability, and quality. Nice to Have * Experience building enterprise AI platforms, Agentic AI solutions, or LLM-powered applications. * Experience integrating enterprise LLM platforms such as Azure OpenAI, OpenAI, Anthropic, or Google Gemini. * Familiarity with vector databases like pinecone, weaviate etc. and AI search technologies, MLOps/LLMOps, and modern AI infrastructure. * Experience implementing data governance, metadata, lineage, and data catalog solutions. * Experience in fintech, payments, procurement, risk, compliance, or enterprise SaaS environments. ## Description * Shape the data platform powering analytics, machine learning, Generative AI, and Agentic AI for millions of customers and internal teams. * Build scalable, cloud-native data infrastructure across batch, streaming, structured, and unstructured workloads using modern engineering best practices. * Partner with Data Science, Machine Learning, Product, and Engineering leaders to deliver AI-ready data products that accelerate innovation across the business. * Influence the future of Zip's Data & AI Platform by driving architecture, mentoring engineers, and establishing the foundations for enterprise-scale AI. * Remote-first opportunity for US-based employees with the option to work in-person out of our Manhattan office., Zip is building the next generation of AI-powered experiences for customers, employees, and partners. As a Senior Data Engineer on the Data & AI Platform team, you will design, build, and scale the data foundation that powers analytics, machine learning, Generative AI, and Agentic AI across the organization. You will develop secure, scalable, and reliable data platforms that support structured and unstructured data processing, real-time and batch workloads, AI-ready data products, and intelligent retrieval capabilities. Working closely with Data Scientists, ML Engineers, Software Engineers, Product teams, and business stakeholders, you will help create a modern data ecosystem that accelerates innovation while maintaining the highest standards of quality, governance, and operational excellence. This is a high-impact role with the opportunity to shape the future of Zip's AI and data platform strategy. What You'll Do * Design, build, and scale Zip's enterprise Data & AI Platform supporting analytics, machine learning, Generative AI, and Agentic AI initiatives. * Develop scalable data pipelines and architectures for structured, unstructured, batch, and real-time data workloads. * Build AI-ready data products, semantic models, and retrieval capabilities that enable intelligent agents and AI-powered applications. * Design and optimize vector search, hybrid search, and Retrieval-Augmented Generation (RAG) capabilities to improve AI effectiveness and user experiences. * Implement streaming and event-driven solutions that support near real-time business insights, operational intelligence, fraud detection, and risk monitoring. * Establish engineering best practices for data modeling, testing, observability, governance, security, and platform reliability. * Drive self-service and automation capabilities that improve developer productivity and accelerate time-to-insight. * Partner with cross-functional teams to deliver trusted, high-quality data solutions that support critical business and AI initiatives. * Mentor engineers, influence architecture decisions, and help define the future direction of Zip's data platform. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. 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