Lead Data Mesh Engineer

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:

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 score this

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

Classification

AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Event StreamingInfrastructure As CodeData MeshCloud ArchitectureFinopsApache KafkaApache NifiTerraform

Questions you could be asked

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