Principal Data Engineer

Axonius

New York (NY)

On-site

USD 180,000 - 260,000

Full time

40 hours ago
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Benefits offered by this job

Competitive compensation
Healthcare premium coverage
Flexible work environment
Paid parental leave
All-company retreats

Job summary

Axonius is seeking a Principal Data Engineer (IC5) to architect scalable, secure enterprise data platforms and drive measurable impact across GTM, Product, CX and Finance. You will own the technical strategy for ETL/ELT pipelines, streaming frameworks like Kafka, and IaC with Terraform, while upholding governance and data privacy standards.

In this high-visibility role, you will lead cross-functional collaboration with executives and teams to deliver proactive, AI-enabled data solutions,

Qualifications

  • Advanced proficiency in SQL and Python for pipeline automation.
  • Proven experience architecting real-time streaming topologies and high-volume data ingestions.
  • 10+ years in data engineering, cloud data architecture or comparable roles.
  • Extensive Terraform experience managing complex warehouse/network configurations.
  • Strong experience with Snowflake data warehouses and multi-region AWS environments.
  • Experience delivering data infrastructure iteratively in Agile environments with Jira.

Responsibilities

  • Serve as principal technical authority for data engineering within the org.
  • Architect, deploy and maintain scalable data platforms across multiple domains.
  • Lead governance, data asset correlation and RBAC/PII masking standards.
  • Implement automated monitoring, cleansing, and schema drift mitigation at ingestion.
  • Partner with IT, Security and Product teams to ensure data reliability and security.
  • Develop AI agent orchestration within the data stack and support ML workflows.

Skills

SQL
Python
Agile
Data modeling

Tools

Terraform
Snowflake
Kafka
AWS

Job description

  • An AI-first global organization operating in a fast-paced environment requires a central data engineering engine, and this role serves that need by using Agile methodologies to architect highly scalable, secure, and reliable enterprise data platforms
  • As a Principal Data Engineer (IC5), you will drive substantial impact on the division’s reputation and technical effectiveness, independently assessing complex scenarios to develop the methods, techniques, and evaluation criteria for obtaining mission-critical results
  • You will provide deep expertise in cloud data infrastructure and pipeline architecture across GTM, Product, CX, Finance, Legal, and People domains, making critical architectural decisions within broadly defined AI first best practices
  • Operating as a highly visible technical leader, you will facilitate collaboration across employees, clients, and senior executives to deliver scalable data solutions before the business even asks for them
  • Formulate and execute the technical architecture strategy for global ETL/ELT pipelines, streaming frameworks (such as AWS Kafka), and infrastructure-as-code (Terraform) deployments to support enterprise-wide AI/ML initiatives
  • Serve as the principal technical authority for the data engineering work group, establishing development standards, code review practices, and evaluation criteria to ensure high pipeline availability and data freshness
  • Architect, deploy, and maintain autonomous AI agents (e.g., Finance Analyst, Data Analyst agents) utilizing LLMs like Claude and Gemini, integrating them directly into the modern data stack for automated insights
  • Independently assess high-risk architectural challenges across GTM, Finance, Product, and other operational domains, making definitive decisions on data warehousing design, upstream schema drift mitigation, and data lake scalability
  • Partner with IT, Security, and Product infrastructure teams on highly specialized governance and architecture matters, including data asset correlation, normalization of disparate source schemas, and the enforcement of global RBAC and PII data masking standards
  • Implement automated data pipeline monitoring, alerting, and automated cleansing mechanisms at the ingestion tier to proactively isolate and fix broken fields or source schema drifts
  • Partner with Analytics Engineering to ensure the stability, scalability, and optimal performance of underlying production-ready repositories feeding the enterprise semantic layer
Benefits
  • Competitive compensation
  • 100% coverage of your healthcare premium
  • Flexible work environment
  • Paid parental leave
  • Annual all-company retreats
  • We offer all this… and more

Advanced proficiency in SQL and software engineering programming languages, specifically Python, for pipeline automation, data scripting, and AI agent orchestration frameworksProven experience independently architecting real-time streaming topologies, high-volume event data ingestions, and custom API-driven connector/adapter frameworks10+ years of experience in data engineering, cloud data architecture, or specialized infrastructure roles, with a proven track record of delivering technical leadership for engineering work groupsExtensive experience designing, provisioning, and tuning production-grade cloud environments using Terraform to manage complex warehouse and networking configurationsExperience delivering data infrastructure iteratively within a fast-paced environment utilizing Agile management tools like JiraStrong hands-on expertise architecting, optimizing, and managing multi-cluster enterprise data warehouses specifically within SnowflakeBackground managing cross-functional technical data requirements and standardizing architectures across GTM, Finance, Product, CX, Legal, and People divisionsDeep experience designing and scaling advanced data platform solutions optimized for machine learning training pipelines, Vector DBs, and operational AI consumptionExperience creating organizational methods, techniques, and governance frameworks to automate data cleansing, quality monitoring, and system resilience at scaleExperience deploying and managing multi-region cloud data infrastructure architectures within AWS enterprise environments

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