Software Engineer (Systems) 3

Responsibilities:

Design and build scalable, distributed Data as a Service that ingest, process, and serve data from robotics, manufacturing, engineering, and clinical sources in real time and batch modes.

Develop and maintain robust APIs, data services, and tooling to provide internal teams with secure, efficient, and intuitive access to high-quality data.

Partner with engineering, analytics, and business stakeholders to evolve data contracts and models that support emerging use cases and ensure semantic consistency.

Implement CI/CD practices for data services, including automated testing for data quality, service reliability, and schema evolution.

Championing a self-service data culture by building discoverable, well- documented data products and guiding teams toward empowered, autonomous data access.

Act as a technical leader within the data domain driving best practices, mentoring teammates, and continuously improving how data is produced, shared, and consumed across the organization.

Qualifications:

Key Skills & Experience:

Solid quantitative background in Computer Science, Engineering, Physics, Math, or 3+ years of hands-on experience in a technically demanding role.

Proficient in at least two major programming languages such as Python, Go, Scala, C++, or Java, with a strong understanding of software design and architecture.

Proven experience building data pipelines and working with distributed systems using technologies like Apache Spark, Kafka, Elasticsearch, Snowflake, and Airflow.

Strong collaborator who actively contributes to code reviews, system design discussions, sprint planning, and KPI evaluations to drive team excellence and technical quality.

Minimum a bachelor’s or master’s degree in computer science, information technology, or a related field.

Bonus Points:

Experience working on Data Platform or Infrastructure Engineering teams.

Hands-on experience with AWS, Docker, Kubernetes, Kafka, Elasticsearch, Apache Airflow, Snowflake, and Terraform.

Familiarity with CI/CD best practices for DataOps and deployment automation.

About the Data Services Team:

We are a rapidly growing organization made up of Software and Data Engineers, with a strong DevOps culture, focused on building a next-generation Data as a Service (DaaS) platform. We are seeking a strong technical lead who is passionate about designing scalable, real-time data systems that deliver high-quality, trusted data across the company.

Our platform leverages technologies such as Apache Kafka for real-time data ingestion, Apache Flink for stream processing and transformation, Snowflake for scalable warehousing, and AWS as our cloud backbone. We focus on serving data via APIs and event streams to enable on-demand access, analytics, and machine learning across product and engineering teams.