Platform Engineer

Carbon Arc; New York, Northern (NY, KY); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Healthcare benefits

Remote work

401(k) plan with employer matching

Paid time off

Parental and family leave

Job summary

Carbon Arc is seeking a Platform Engineer to design, build, and maintain the data platform powering our analytics products. You will craft scalable ETL pipelines, implement workflow orchestration, and develop internal tooling for reliability and speed.

The role emphasizes Python development, data quality controls, and collaboration on platform architecture in a fast-paced startup environment. Remote-first with on-site collaboration as needed.

Qualifications

• 3–5+ years building data systems or platform engineering.
• Proficient in Python with strong testing and code quality.
• Experience designing and operating ETL pipelines and DAG-based workflows.

Responsibilities

• Design and build large-scale ETL/ELT pipelines from massive data sources.
• Develop and maintain workflow orchestration with Airflow or similar systems.
• Write clean, well-tested Python code for data and infra challenges.
• Create internal tools to boost developer productivity and reliability.
• Implement data quality monitoring with traceability to sources.
• Define schemas, partitions, and indexes for performance needs.
• Query optimization for analytical databases.
• Contribute to platform architecture and best practices.
• Debug distributed data system issues and document procedures.

Skills

Python

Spark

ETL pipelines

Airflow

SQL

AWS

Data quality

Data orchestration

Tools

Airflow

Dagster

Prefect

Kubernetes

Terraform

Job description

This role is an opportunity for a talented Platform Engineer to join a growing engineering team and help build the foundation of Carbon Arc's data platform. You will design, build, and maintain the systems that power our data intelligence products, spanning large-scale data pipelines, workflow orchestration, and internal tooling that keeps the platform reliable and scalable.

You will thrive in this role if you enjoy working in a fast-paced startup environment where your decisions have meaningful technical and product impact. If you care deeply about building reliable data systems and writing clean, well-tested code, this role offers a wide range of challenging and high-impact problems.

What You'll Do

• Design and build performant ETL/ELT pipelines for massive data sources, including terabytes of structured and unstructured data
• Develop and maintain workflow orchestration using Airflow or similar DAG-based systems
• Write clean, well-tested Python code to solve data and infrastructure challenges
• Build internal tooling and automation to improve developer productivity and pipeline reliability
• Implement data quality monitoring with traceability back to source systems
• Define schemas, partitions, and indexes aligned to usage patterns and performance needs
• Create, optimize, and maintain queries against analytical databases
• Collaborate on platform architecture decisions and help establish engineering best practices
• Debug complex issues across distributed data systems and services
• Document systems, pipelines, and operational procedures to support long-term scalability

What You'll Bring

• 3–5+ years of software engineering experience with a focus on data systems or platform engineering
• Experience with Spark or other distributed data processing frameworks
• Strong proficiency in Python, with an emphasis on testing and code quality
• Deep experience building and operating ETL pipelines, data quality controls, and workflow orchestration systems (Airflow, Dagster, Prefect)
• Hands-on experience with AWS services such as S3, IAM, Glue, EMR, and RDS
• Familiarity with data lake architectures, Apache Iceberg, and data catalogs
• Strong SQL skills, including query optimization and partitioning strategies
• Comfort integrating AI-assisted development tools into daily workflows to accelerate productivity
• Strong written and verbal technical communication skills
• A proactive mindset with the ability to adapt quickly and drive change in evolving systems

Nice to Have

• An active GitHub profile showcasing personal or open-source projects in data or platform engineering
• Experience with MLOps, feature stores, or machine learning pipeline orchestration
• Kubernetes/EKS and container orchestration experience
• Familiarity with infrastructure-as-code tools such as Terraform
• Experience with GitOps workflows (e.g., ArgoCD)
• Experience with analytical databases such as StarRocks, ClickHouse, Trino, or Snowflake
• Exposure to data security, compliance, and access management frameworks (e.g., SOC 2)
• Experience with zero-trust networking solutions such as Tailscale

What We Offer

• Fully paid healthcare benefits (Medical, Dental, Vision)
• Remote work options
• 401(k) plan with employer contributions
• Paid time off
• Generous parental and family leave policies
• Challenging problems to tackle with a supportive, entrepreneurially driven team
• A strong work culture centered on integrity, excellence, truth, trust, and transparency

Location

Carbon Arc is headquartered in New York City and operates as a remote-first company. Team members are expected to travel for in-person onsite gatherings at least one week per quarter to collaborate, plan, and connect as a team.

Equal Opportunity Employer

Carbon Arc is an Equal Opportunity Employer and is committed to fair and equitable hiring practices. All hiring decisions are based on strategic business needs, job requirements, and individual qualifications. All candidates are considered without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, pregnancy, veteran or military status, citizenship status, or any other characteristic protected by applicable federal, state, or local law.

Accommodations

Carbon Arc is committed to providing reasonable accommodations throughout the hiring process for qualified individuals with disabilities. If you require an accommodation to participate in the application or interview process, please contact us at [e-mail] .