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Cloudera

Lead Data Mesh Engineer

Cloudera is hiring a Lead Data Mesh Engineer. Level rates it ; you can apply on Cloudera.

Level's read on this job

  • Level rates this role Little AI ●○○○: aI is not part of the work.
  • Some of the work can be done remotely, according to the posting.
  • The posting mentions Apache Kafka, Apache Nifi and Terraform among its tools and skills.
  • Level classes it as a lead role.
  • Cloudera has 51 other open roles on Level.

AI in this role

Architect and deliver enterprise-grade data mesh and event-streaming infrastructure using Kafka and Kubernetes.

Apache KafkaApache NifiTerraformKubernetesAWSGitops
event-streaminginfrastructure-as-codedata-meshcloud-architecturefinops

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

How we rate this

Lead Data Mesh Engineer at Cloudera rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Event StreamingInfrastructure As CodeData MeshCloud ArchitectureFinopsApache KafkaApache NifiTerraform

Questions you could be asked

  1. Tell me about a project where event streaming was part of your work. What did you do?
  2. Tell me about a project where infrastructure as code was part of your work. What did you do?
  3. Tell me about a project where data mesh was part of your work. What did you do?
  4. Tell me about a project where cloud architecture was part of your work. What did you do?
  5. Tell me about a project where finops was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Event Streaming, Infrastructure As Code, Data Mesh, Cloud Architecture, and Finops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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