Job Description
The Experimentation & Insights team is a lean group within Observability & Performance charged with developing, operating and ensuring the smooth operation of an Experimentation platform that we dub “Houston”, as the launchpad for all Slack features. This is one of the most impactful teams in the company as every Slack feature is rolled out through Houston, and we base all product decisions on insights derived from our deep and rich set of product metrics. We aim to enable rapid product innovation and iteration through data-informed decision making!
Our team is distributed throughout the US , Canada, and we have a multifunctional team of backend & frontend developers, data engineers, as well as a dedicated product manager.
About the Role
This is a Staff Technical Lead Manager role, which is a flexible mix of people management and technical hands-on work, allowing you to enjoy the best of both worlds! We are looking for people who are passionate about product experimentation and running an experimentation platform to enable Slack to rapidly develop and release impactful features.
As a Staff TLM, you like building for the long term and value patterns and structures that allow for maximum flexibility in a constantly evolving product. You excel in leading a small team (~3-4 engineers) through mentoring them to develop into technical leaders. You set a high bar for the technical design and code quality of your org. You demonstrate outstanding ownership of not only the area of your team, but in multiple functional areas such as data pipelines, data schema governance and experimental statistics. You possess a “can do” demeanor and nothing is beneath you or outside your responsibilities because you do what it takes to deliver the highest quality code and the most impactful features.
What you will be doing:
Develop team governance and rituals, establish and run regular meetings
Work with our product manager to build a vision and develop the roadmap for Experimentation at Slack.
Mentor engineers on the team with an eye for excellence and technical leadership
Build, maintain and supervise team health metrics and product health metrics, e.g. Houston experiment runtime, experiment reliability and metrics pipeline health.
Ensure the team is well-staffed by hiring top talent, and using performance management to ensure engineering excellence.
Work with stakeholders to ensure needs are met and that there is alignment between customers of Houston and the team.
Build, maintain and ensure availability of our Experimentation platform, Houston.
Develop product & technical specifications for impactful features and work with engineers on the team to complete projects.
What you should have:
Experience building and operating internal tools for product development, e.g. experimentation platforms, feature flag/toggle platforms, or release platforms.
Understanding of quantitative and qualitative data concepts as well as concepts around experimentation, such as statistical significance, p-value, minimal detectable effect, applying statistical tests to a null hypothesis, as well as pitfalls in misleading data or improper instrumentation leading to unbalanced or biased results.
You are a strong communicator. Explaining sophisticated technical concepts to designers, support, and other engineers is no problem for you.
You enjoy helping onboard new team members, mentoring, and guiding others.
You live for unit tests, code review, design documentation, debugging, and solving problems.
You have a deep curiosity about how things work under the hood.
You are motivated by helping others succeed. When things break — and they will — you are eager and able to help fix things. You like thinking of ways to improve efficiency or bring delight to your coworkers.
You care about improving the performance of systems through data-informed decisions.
You also know that the internet is a scary place and understand security concepts deeply and can put them into action to protect us and our users.
Firm grasp of computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.
Nice to Have:
Direct experience building and operating an internal experimentation platform at scale.
Solid competency with Airflow DAG (Directed Acyclic Graphs) data processing jobs or other stream/batch processing suites.
Proven competency in Typescript, Hacklang, PHP, and/or Scala
Degree or formal training in statistics, applied math or other relevant areas.
Experience at large scale with high volume data pipelines, distributed systems, or distributed databases.
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