Software Engineer

Description

The company is building a modern, scalable Data as a Service platform that feeds its digital products and serves more than 2,000 engineers across the organization.

You will own and improve key parts of the real-time and micro-batch data pipelines used for product development, internal tools, and analytics.

You will work on high-throughput, low-latency data delivery using streaming pipelines, dynamic transformations, and APIs, making data easier to find, reach, and act on.

You will help set the architecture and engineering practices behind self-service analytics and day-to-day operational decisions at scale.

The goal is to replace legacy processes with modern systems so teams can move faster, with more confidence and independence.

Responsibilities

• Design and build scalable, distributed Data as a Service that ingests, processes, and serves data from robotics, manufacturing, engineering, and clinical sources in both real-time and batch modes.
• Develop and maintain APIs, data services, and tooling that give internal teams secure, efficient, and easy access to high-quality data.
• Work with engineering, analytics, and business stakeholders to evolve data contracts and models for new use cases while keeping meanings consistent.
• Set up CI/CD for data services, including automated tests for data quality, service reliability, and schema changes.
• Build discoverable, well-documented data products and help teams access data on their own.
• Lead technically within the data domain by setting best practices, mentoring teammates, and improving how data is produced, shared, and used across the organization.

Requirements

• Strong quantitative background in computer science, engineering, physics, or math, or at least 3 years of hands-on experience in a technically demanding role.
• Proficiency in at least two major programming languages, such as Python, Go, Scala, C++, or Java, with a solid grasp of software design and architecture.
• Proven experience building data pipelines and working with distributed systems using tools such as Apache Spark, Kafka, Elasticsearch, Snowflake, and Airflow.
• A collaborative approach, including active contribution to code reviews, system design discussions, sprint planning, and KPI reviews to raise team quality.
• A bachelor's or master's degree in computer science, information technology, or a related field, at minimum.
• Bonus: experience on Data Platform or Infrastructure Engineering teams.
• Bonus: hands-on experience with AWS, Docker, Kubernetes, Kafka, Elasticsearch, Apache Airflow, Snowflake, and Terraform.
• Bonus: familiarity with CI/CD practices for DataOps and deployment automation.

Conditions

The company and/or its customers may require current proof of vaccination against certain diseases, including COVID-19, depending on the role.

Roles subject to U.S. export controls may need an export license or a Technology Control Plan before the start date. Licensing can take 3 to 6+ months and a TCP typically adds 2 weeks, and final offers depend on that approval.

Qualified applicants with arrest and conviction records will be considered in line with fair chance laws.

Preference goes to qualified candidates who do not live, and do not plan to live, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.

The job level may differ from the one listed, depending on business need and the selected candidate's experience, knowledge, and skills.

Pay is based mainly on the job level the role is filled at and the candidate's qualifications, within legal limits.