Software Engineer, Large-Scale Data Systems

We are looking for a Software Engineer to join team Aqueduct, a team building our data platform for powering large-scale cross-platform advertising. Our ideal candidate is a professional who has experience in the domain of data engineering, and knows how to design, implement and maintain data storages and pipelines using industry standard tools.

For our customers, ensuring their data is available and composable can:

• unlock the potential of creative automation with image and video templates

• power agentic workflows that utilise the data

• allow analysis of the relationship between product data and ad performance.

Being able to sync our customers’ product data across multiple advertising channels consistently and with minimal delays ensures that:

• the ads consumers see have the latest information

• products that are out of stock are not advertised

• regulatory requirements are met

The team currently has a backend written in Ruby on Rails, and we own small parts of the frontend written in TypeScript and React. We’re moving our data systems from Ruby to a language and architecture better suited for the workload and capable of scaling with our growth. We're looking for an experienced engineer to join the team and contribute to the build and design of this new platform using the right tools for the job.

What You Will Do

• Build a large scale data storage and processing system that needs to process billions of records per day

• Contribute to the architecture and engineering excellence inside the team by collaborating with other engineers

• Collaborate with stakeholders from across the organization: engineering, product and business

• Participate in defining and monitoring SLAs, and follow SRE best practices to ensure the stability and availability of the system

• Build APIs for internal and external consumers of the data

• Affect the ROI for billions of dollars in ad spend

What We Are Looking For

• 3-5 years of industry experience

• Strong programming skills (e.g., Python, Scala and/or Java)

• Some experience with data processing frameworks (e.g., Spark, Flink, Databricks, Snowflake, BigQuery, Redshift, ClickHouse)

• Familiarity with streaming systems (e.g Kafka, Kinesis)

• Experience with SQL and some RDBMS (PostgreSQL, Citus, etc.)

• Experience contributing to large-scale data systems

• Experience with Ruby on Rails is considered a plus