# Staff Data Platform Engineer

**Company:** [Honor](https://hotfix.jobs/companies/honor)
**Location:** Remote
**Role:** Data Engineering
**Salary:** $194k – $220k/yr
**Experience:** 8+ years
**Skills:** Python, Amazon Redshift, Aws Cdk, Airflow, dbt, Datadog, Fivetran, Aws Dms, Zeroetl, Data Governance
**Posted:** 2026-06-08

> Staff Data Platform Engineer building and leading AWS-native data platform architecture, orchestration, governance, and AI-readiness for analytics and ML workloads. Requires 8-10+ years experience with AWS data systems and strong technical leadership.

## Job Description

## Build and Evolve Our AWS-Native Data Platform
- Lead the architecture and development of scalable, secure, and cost-efficient data platforms on AWS.
- Architect and optimize our Data Warehouse to support growing analytical, operational, and AI-driven workloads.
- Define and implement Infrastructure-as-Code standards using AWS CDK.

## Own Data Orchestration and Data Engineering Foundations
- Design and operate scalable orchestration frameworks using Airflow and Fivetran.
- Partner with the Data Analytics team to establish data modeling standards and transformation practices using dbt.
- Build reusable, maintainable data pipelines and workflows that enable rapid development and reliable operation.

## Enable Trusted Data Access Through Governance and AI Readiness
- Establish governance, metadata, lineage, and access patterns that make data discoverable, trustworthy, and easy to use.
- Help define how both employees and AI-powered systems safely access and leverage company data.
- Build the foundations that enable self-service analytics and future agentic workflows across the organization.

## Drive Reliability, Observability, and Operational Excellence
- Establish monitoring, alerting, and observability standards using Datadog and modern platform engineering practices.
- Build scalable data quality frameworks that ensure confidence in business-critical data.
- Continuously improve platform reliability, performance, and cloud cost efficiency.

## Lead Through Technical Influence and Partnership
- Partner closely with Data Science, Analytics, Product, and Engineering teams to solve complex business problems through data.
- Provide technical leadership, architectural guidance, and mentorship across the data organization.
- Influence long-term platform strategy and engineering best practices across multiple teams.

## What We're Looking For
- 8–10+ years of experience building and operating large-scale data platforms, pipelines, and warehouses in cloud environments, with deep expertise in AWS.
- Proven track record leading complex technical initiatives and influencing architecture across teams.
- Strong software engineering fundamentals and experience building production-grade systems.
- Deep expertise in modern data warehousing, ELT/ETL architectures, and data platform design.
- Experience operating data platforms with a focus on reliability, observability, data quality, and cost optimization.
- Proven ability to leverage modern AI-assisted and agentic development tools to architect, build, and operate production-grade systems.
- Experience partnering with data scientists, analysts, product managers, and software engineers to deliver business impact.
- Demonstrated ability to navigate ambiguity, drive alignment, and lead through influence rather than authority.
- Passion for building platforms that empower others and scale organizational impact.

## Preferred Qualifications
- Strong hands-on experience with Python, Amazon Redshift, AWS-native ETL technologies (including ZeroETL and DMS), Airflow, dbt, Datadog, Fivetran, and AWS CDK.
- Experience designing data governance, metadata, lineage, or self-service data platforms.
- Experience supporting AI, machine learning, or agentic workflow initiatives.
- Experience leading platform modernization efforts in high-growth environments.
- Experience as a Staff Engineer, Principal Engineer, Technical Lead, or Engineering Manager.

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