Principal Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and implement the technical architecture strategy for global ETL/ELT pipelines, streaming frameworks like AWS Kafka, and Terraform infrastructure-as-code deployments for enterprise-wide AI/ML projects.

• Act as the primary technical authority for the data engineering team.

• Set development standards, establish code review processes, and define evaluation criteria.

• Design, deploy, and maintain autonomous AI agents utilizing LLMs such as Claude and Gemini.

• Seamlessly integrate AI agents into the modern data stack to facilitate automated insights.

• Evaluate high-risk architectural challenges across GTM, Finance, Product, and additional operational domains.

• Make architectural decisions regarding data warehousing, schema drift mitigation, and data lake scalability.

• Collaborate with IT, Security, Product infrastructure, and Analytics Engineering teams on governance, architecture, repository stability, scalability, and performance.

• Implement automated monitoring of pipelines, alerting systems, and ingestion-tier data cleansing strategies.

• Identify and rectify broken fields and source schema drift.

• Enforce global RBAC and PII data masking protocols.

⛳️ Requirements

• Over 10 years of experience in data engineering, cloud data architecture, or specialized infrastructure roles.

• Demonstrated history of providing technical leadership for engineering teams.

• Advanced expertise in SQL.

• Advanced skills in Python for pipeline automation, data scripting, and AI agent orchestration frameworks.

• Significant experience in designing, provisioning, and optimizing production-grade cloud environments using Terraform.

• Experience in independently architecting real-time streaming architectures.

• Familiarity with high-volume event data ingestion.

• Experience in developing custom API-driven connector/adapter frameworks.

• Preferred: Knowledge of Agile management tools, such as Jira.

• Preferred: Expertise in Snowflake.

• Preferred: Experience managing cross-functional technical data requirements and standardizing architectures.

• Preferred: Background in machine learning training pipelines, Vector DBs, and operational AI.

• Preferred: Experience in data cleansing, quality monitoring, and system resilience frameworks.

• Preferred: Familiarity 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

• Stock options.

• Comprehensive benefits package.

• Annual bonus.

• Competitive salary.

• Opportunities for professional growth.

• Community-building initiatives.