Sr. Engineer, Data & Cloud Infrastructure

Trace Air Quality, Inc; Salt Lake City, Northern (UT, KY); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Trace Air Quality, Inc. is seeking a Sr. Engineer, Cloud Infrastructure & Data Science to join as an early strategic hire. You will help build Trace AQ’s distributed forecasting systems, migrating the Air Quality Analytics engine to cloud infrastructure and shaping cloud-native components.

You will design reliable distributed systems, implement large data pipelines, and mentor junior engineers while exploring AI tooling to enhance product and infrastructure.

Qualifications

• 8+ years in software development and distributed systems.
• Experience with cloud development, ideally AWS.
• Proficiency in multiple languages; ability to up-level quickly.
• Experience with containerization (Docker) and orchestration (Kubernetes).

Responsibilities

• Architect and implement Trace Air Quality’s distributed forecasting systems.
• Lead migration of Air Quality Analytics engine to cloud infrastructure.
• Design reliable distributed systems and core platform decisions.
• Build cloud-native components of the AQA engine.
• Develop and maintain large-data pipelines and data sources.
• Apply distributed tracing and performance monitoring.
• Guide DevOps practices and mentor junior engineers.
• Explore AI tooling opportunities to enhance product and infrastructure.

Skills

Cloud infrastructure

Distributed systems

Data pipelines

DevOps best practices

AWS

Programming languages

Communication skills

Agile methodologies

Mentoring

Tools

Docker

Kubernetes

SQL

NoSQL

Linux

Kafka

Spark

Terraform

Job description

Overview

We are seeking someone who is passionate about building. If our mission to deliver the world’s best air quality solutions resonates with you this position may be for you. The Sr. Engineer, Cloud Infrastructure & Data Science will be an early strategic hire at Trace AQ helping build the engineering team. We are looking for a highly qualified and experienced Software Engineer with a focus on data pipelines and cloud infrastructure to build and manage Trace Air Quality’s distributed forecasting systems. The ideal candidate will have a deep understanding of development on the cloud, data pipelines, and distributed systems. This role will be instrumental in shaping our company's future and driving advancements in air quality technology.

To succeed in this position, candidates will need to be comfortable with the demands of a high-growth startup and have an energetic and problem-solving mindset. Experience at an early-stage, high-growth company will be very helpful in this position.

Trace Air Quality is an equal-opportunity employer.

What we're looking for

Responsibilities

Architect and implement Trace Air Quality’s distributed forecasting systems:

Lead the effort to transition the Air Quality Analytics (AQA) Engine fully to cloud infrastructure.

Architect reliable distributed systems and guide decisions around fundamental primitives and platforms.

Build future components of the AQA engine in a cloud native manner.

Implement complex data pipelines which process large amounts of data.

Implement distributed tracing and performance monitoring.

Expand and maintain forecast engine data sources:

Implement efficient retrieval of large quantities of public and private atmospheric data.

Efficiently store data for future use.

Build cloud infrastructure and DevOps practices:

Implement scalable cloud systems using modern IaC tools.

Guide the team and mentor junior engineers in implementing cloud best practices.

Expertise in using and working with AI tools

Ability to guide the engineering team’s use of AI tools

Vision to find opportunities to use AI tools to better the product and infrastructure

Drive to stay ahead of the learning curve on AI capabilities, best practices, and intuition to help guide the company’s use of AI

Required Qualifications

Experience with cloud development, ideally AWS

Proficiency in multiple programming languages and ability to quickly up-level in new languages

Skilled in containerization (Docker) and orchestration (Kubernetes).

Proficient in SQL and/or NoSQL database systems (e.g., MySQL, PostgreSQL).

Experience with Linux, and compiling static binaries.

Excellent communication and presentation skills.

Ability to work within and manage various DevOps and Agile systems.

8+ years of hands-on experience in software development and distributed systems or equivalent proficiency

Additional Desired Qualifications

Interest in data science, atmospheric forecasting, and machine learning

Experience with machine learning and statistical modeling techniques.

Experience in FORTRAN, R, python, C++, and/or Java.

Experience using distributed message queues/logs (such as Kafka) and distributed data analytics engines (such as Spark)

Trace Air Quality Values

The Best & Brightest - Our strength is our people and team. Big imaginations, passionate souls, and tenacious spirits aligned to create, build, and help each other.

Think Big - We aim to tackle difficult problems to leave things better than we found them. We are never afraid to take on a challenge and we’re bold enough to challenge what others think is impossible.

Results Driven - We use world-class science and technology to create incredible value for the communities, businesses, and people we serve.

About Trace Air Quality

Trace Air Quality is on a mission to deliver the world’s best air quality solutions. With a deep understanding that air quality directly impacts every person's quality of life, Trace AQ uses it’s foundation in cutting-edge data science to provide actionable insights to businesses, agencies, and consumers. By transforming complex environmental data into simple, reliable insights and alerts, Trace AQ empowers its users to make informed decisions in the face of rapidly changing air quality conditions. Specializing in the forecasting of smoke, dust, inversions, and other air quality hazards, Trace AQ sets the standard for accurate, timely, and industry-leading air quality intelligence.