Principal Data Engineer

Axonius

. Formulate and execute the technical architecture strategy for global ETL/ELT pipelines, streaming frameworks such as AWS Kafka, and Terraform infrastructure-as-code deployments for enterprise-wide AI/ML initiatives .

Posted 10/8/2026full-timeRemote • United StatesLead💰 $171,000 - $190,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in formulating and executing technical architecture strategies for ETL/ELT pipelines and AI/ML initiatives, with advanced proficiency in SQL and Python for data engineering and automation. Capable of leading cross-functional teams and establishing development standards while ensuring data governance and compliance.

Highest-signal resume keywords

Data EngineeringCloud Data ArchitectureSQL ProficiencyPython AutomationTerraform Infrastructure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT PipelinesAI Agent OrchestrationReal-Time Streaming ArchitecturesData WarehousingSchema Drift MitigationData Lake ScalabilityAPI-Driven Connector DevelopmentData CleansingQuality MonitoringMachine Learning Pipelines

Soft Skills

Technical LeadershipCollaborationProblem Solving

Tools & Technologies

AWS KafkaTerraformJiraSnowflake

Industry Keywords

RBACPII Data MaskingCloud InfrastructureData GovernanceOperational AI

Tech Stack

Tools & technologies

AWSCloudETLKafkaPythonSQLTerraform

About the role

Key responsibilities & impact

Formulate and execute the technical architecture strategy for global ETL/ELT pipelines, streaming frameworks such as AWS Kafka, and Terraform infrastructure-as-code deployments for enterprise-wide AI/ML initiatives
Serve as principal technical authority for the data engineering work group
Establish development standards, code review practices, and evaluation criteria
Architect, deploy, and maintain autonomous AI agents using LLMs such as Claude and Gemini
Integrate AI agents into the modern data stack for automated insights
Assess high-risk architectural challenges across GTM, Finance, Product, and other operational domains
Make architectural decisions on data warehousing, schema drift mitigation, and data lake scalability
Partner with IT, Security, Product infrastructure, and Analytics Engineering teams on governance, architecture, repository stability, scalability, and performance
Implement automated pipeline monitoring, alerting, and ingestion-tier data cleansing mechanisms
Isolate and fix broken fields and source schema drift
Enforce global RBAC and PII data masking standards

Requirements

What you’ll need

10+ years of experience in data engineering, cloud data architecture, or specialized infrastructure roles
Proven track record of delivering technical leadership for engineering work groups
Advanced proficiency in SQL
Advanced proficiency in Python for pipeline automation, data scripting, and AI agent orchestration frameworks
Extensive experience designing, provisioning, and tuning production-grade cloud environments using Terraform
Experience independently architecting real-time streaming topologies
Experience with high-volume event data ingestions
Experience developing custom API-driven connector/adapter frameworks
Preferred: Experience using Agile management tools like Jira
Preferred: Expertise with Snowflake
Preferred: Experience managing cross-functional technical data requirements and standardizing architectures
Preferred: Experience with machine learning training pipelines, Vector DBs, and operational AI
Preferred: Experience with data cleansing, quality monitoring, and system resilience frameworks
Preferred: Experience with multi-region AWS cloud data infrastructure
Must be eligible to work in the United States, as indicated by the USA location and E-Verify participation

Benefits

Comp & perks

Stock options
Attractive benefits
Annual bonus
Competitive compensation
Growth opportunities
Community-building