Data Engineer

The Role

Reporting to the VP of Engineering who leads the development of our next generation platform, you will build the data platform that everything else at Everseen depends on. Our models are only as good as the data behind them, and this role owns the pipelines, stores and streams that turn six petabytes of daily video and event data into something teams can utilize. You will work with the latest tooling in the data space and on real time streaming systems that feed live models across thousands of stores. This is a high impact role at the center of the team who are building the next generation platform. This is an ideal role if you enjoy building data systems that hold up under real load and innovating in a fast paced iterative environment.

This role will allow you to take your career to the next level, working alongside industry experts and scaling a successful global organization.

Our Technology Stack

Our engineering teams at Everseen have the opportunity to work with and develop skills across a modern, high-performance tech stack:

• Languages: Python, C/C++, CUDA (for GPU-accelerated computing)
• AI/ML & Computer Vision: PyTorch, OpenCV, TensorRT, ONNX
• Tools & Infrastructure: Linux, Docker, Kubernetes, Git, and CI/CD pipelines
• Data & Streaming: Real-time video processing, RTSP/video streaming, and cloud platforms

What you’ll do

• Design and build the data pipelines and platform that power model training, evaluation and real time inference across Everseen’s products.
• Ownership of relevant data modeling activities, including conceptual, logical, and physical data modeling, to ensure data structures align with business requirements and analytical use-cases.
• Work with the product and engineering teams to design and implement advanced, cloud-based data lake-house solutions
• Build and run streaming, real time data applications that move event and video-derived data from stores to the platform with low latency.
• Model, store and serve large volumes of data on Snowflake and Databricks, and keep it reliable, queryable and cost aware.
• Work with applied science and platform teams to give them clean, well documented datasets and features they can trust.
• Own data quality, lineage and observability so problems get caught early rather than in production.
• Optimize storage, compute and query patterns as data volumes grow, and make sensible trade-offs between cost and performance.
• Drive alignment with cross-functional teams, including product, engineering, and executive leadership.Contribute to shared tooling and standards, review work, and help lift how the team handles data.
• Keep an eye on new tools in the data and streaming space and bring in the ones that earn their place

Collaborating With

You will work closely with applied science engineers, platform and infrastructure engineers, MLOps engineers, product managers and analytics teams, along with the operations teams that run our software in customer environments.

Profile and Skills

• 3-5 years building data platforms or pipelines in production, ideally at scale.
• Deep understanding of data modeling, performance tuning and cost management.
• Strong hands-on experience with Snowflake and Databricks.
• Proven experience building streaming and real time data applications with tools such as Kafka, Spark Structured Streaming or Flink.
• Proven programming skills in Python and SQL for building data pipelines, performing data transformations, and implementing automation tasks. Comfortable with the software engineering practices that keep data systems maintainable.
• Solid understanding of distributed systems, data warehousing and lakehouse patterns.
• Experience with large scale video or event data, or other high volume sources, is a strong advantage.
• Familiarity with cloud platforms, Docker, Kubernetes and CI/CD for data workloads.
• A pragmatic approach to data quality, reliability and observability. You build things that do not keep people awake at night.
• Excellent communication skills and the ability to work closely with the teams that consume data. You like to share your skill, knowledge and expertise across your team and the wider organization.
• You enjoy solving complex problems creatively and you like to work independently in a fast moving, delivery focused team.
• Bachelor’s or Master’s degree in Computer Science, Engineering or a related field, or equivalent practical experience.