Lead Data Mesh Engineer

Job description

Business Area: IT Seniority Level: Mid-Senior level Job Description: At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. About the Team & Role We are building an enterprise-grade, Everything-as-Code (EaC) Data Mesh that transforms corporate IT from a manual ticket-driven delivery model into an automated, machine-executable software factory. As the Lead Data Mesh Engineer , you will own the architectural execution and hands-on delivery of our high-throughput, asynchronous event-streaming infrastructure and hybrid data pipelines. Operating in an environment where every asset, route, and policy must exist as declarative code inside Git, you will architect the "Data-in-Motion" backbone across multi-cloud environments (AWS MSK, Apache NiFi on EKS) and insulate our core on-premises data lakehouse. As a Lead Data Mesh Engineer, you will: Event-Streaming Architecture (IaC): Architect, provision, and maintain multi-AZ Amazon Managed Streaming for Apache Kafka (AWS MSK) clusters and Apache NiFi runtimes on Amazon EKS (Graviton ARM64) using Terraform and declarative GitOps patterns. Contract-First Schema Governance: Integrate vendor-neutral Schema Registries (AWS Glue / Apicurio) to enforce strict Apache Avro and AsyncAPI data contracts defined in our central Governance Hub before payloads hit production event topics. Egress & FinOps Optimization: Implement high-performance partition strategies, dynamic storage auto-scaling (gp3/io2), and mandatory local payload compression (Snappy/Zstd) to minimize cross-cloud data movement fees and optimize compute consumption. Resiliency & Out-of-Band Telemetry: Build fault-tolerant Dead Letter Queue (DLQ) automated replay loops and ensure all streaming payloads carry lightweight, out-of-band tracing context across service hops. We are excited if you have (Required Experience): Bsc/Msc in related field or equivalent experience Core Streaming & Orchestration: 6+ years of deep, hands-on experience architecting and operating Apache Kafka (preferably AWS MSK) and Apache NiFi in containerized Kubernetes environments (EKS). Infrastructure-as-Code & GitOps: Advanced proficiency with Terraform and GitOps deployment tools (ArgoCD or Flux) operating under a strict pull-based model. Data Serialization & Contracts: Expertise in Apache Avro , AsyncAPI , and schema registry management for Master Data Management (MDM) enforcement. Hybrid Mesh & Lakehouse Integration: Demonstrated background connecting cloud event meshes to enterprise data lakehouses or big-data monoliths (Cloudera CDP, Hadoop, Hive). Distributed Observability: Practical understanding of out-of-band telemetry exhaust, OpenTelemetry standards, and W3C distributed tracing context propagation. You may also have: Exposure to Policy-as-Code tools (Open Policy Agent / Rego). What you can expect from us: Generous PTO Policy Support work life balance with Unplugged Days Flexible WFH Policy Mental & Physical Wellness programs Phone and Internet Reimbursement program Access to Continued Career Development Comprehensive Benefits and Competitive Packages Paid Volunteer Time Employee Resource Groups EEO/VEVRAA #LI-EO1 #LI-HYBRID