DescriptionAt Secret Sauce Partners, we work with some of the largest retailers and marketplaces in the world to transform how people shop online. We combine data from retailers with data we create using AI and machine learning to power innovative and powerful retail technologies.
As the Director of Engineering, you will have the opportunity to lead the team responsible for building, running, and maintaining our services integrated into high-traffic e-commerce websites and used by tens of millions of people.
What you'll be working on
- Manage the Engineering team consisting of engineers and team leads, develop and maintain the team's culture
- Lead new feature development, maintenance, and operation activities
- Optimize operational efficiency by effectively managing projects and resources
- Facilitate design and architecture discussions and decision-making to ensure business requirements are translated into working software systems
- Collaborate with product management to translate company strategy and goals to the execution level
- Contribute to strategic planning
- Conduct 1:1s and provide regular feedback to support the professional development of the team members
- Facilitate transparency and open communication among team members and cross-functionally
Who you'll be working with
- A smart and highly capable team that builds and runs large-scale SaaS products rolled out to customers in all corners of the world
- A product team that thrives on data-driven decisions for products with 100+ million users
Requirements- At least 5 years of experience in managing software engineering teams with a history of leading engineers of various backgrounds
- Min 5 years experience as a senior engineer or tech lead, with a track record in backend- and data-heavy projects, using Java and/or Python
- Demonstrated leadership in engineering management, with a proven ability to lead teams through complex projects
- Track record of operational excellence, using agile methodologies
- Deep understanding of the software development process, development practices, and principles
- Excellent communication skills in English
Bonus points
- You have built scalable data processing pipelines before
- You have worked on building and operating a cloud-based SaaS
- You have worked on scaling teams in a start-up environment
- You have experience in building and leading remote teams
If the role sounds interesting, apply now and get to know us during the interviews. You can read more about our hiring process on Glassdoor.
Tech StackAt Secret Sauce, we use the technologies and tools that we believe are right for the job at the time. We're not afraid to replace a technology or rewrite a service if gaining experience and understanding the domain better makes us realize that we made the wrong choice. We embrace change and work in a fast-paced environment which means that the technology stack we work with is what we believe is the best. That makes us quite happy.
Our backend system consists of independent services built using Java and Python that communicate asynchronously through Kafka. We use Avro and a Schema Registry to enforce these interfaces. All our services are packaged using Docker and deployed to our infrastructure in AWS using Kubernetes. Our infrastructure is immutable, we build AMIs with Packer and roll them out with Terraform. We don't have "DevOps" or an Ops team, we think of running services in a cloud environment as part of the software engineering role.
The services we provide to our retail partners are integrated into their existing websites; we provide a single JavaScript library that they can use to unlock all of our products. Analytics, AB testing, error reporting, real-user monitoring is built-in and is available to Fit Predictor, Style Finder, and our future services. The services themselves are built using modern JavaScript, React, and Svelte.
Our data team loves Spark and uses it to process large datasets that we receive from our partners and that we produce ourselves. We don't run a persistent cluster; we process and move data between different data stores: S3, Kafka, PostgreSQL, and Snowflake are all part of the equation and are used where they make the most sense. We rely on Databricks to manage our Spark clusters and use Apache Airflow to orchestrate tasks and to monitor, schedule, and retry jobs.
We started out as a small development team using Ruby and Rails. We ended up with our current architecture and tech stack not because we use technology for technology's sake, but because we believe they are the right choice with the right trade-offs for our expertise, needs, and size.
