Who are we? 👋

Toplyne is a global SaaS product built to help revenue teams, at businesses with a self-service motion, and a large user-base, identify which users to spend time on, when and for what outcome. Think self-service or freemium-led companies like Figma, Notion, Freshworks, and Slack. We do this by helping companies recognize signals across their - product engagement, sales, billing, and marketing data.

Founded in June 2021, Toplyne is backed by marquee investors like Sequoia,Together fund and a bunch of well known angels. You can read more about us on - https://bit.ly/ForbesToplyne , https://bit.ly/YourstoryToplyne.

What will you get to work on? 🏗️

• Design, Develop and maintain scalable data pipelines and Data warehouse to support continuing increases in data volume and complexity.
• Develop and implement processes and systems to supervise data quality, data mining and ensuring production data is always accurate and available for key partners and business processes that depend on it.
• Perform data analysis required to solve data related issues and assist in the resolution of data issues.
• Complete ownership - You’ll build highly scalable platforms and services that support rapidly growing data needs in Toplyne. There’s no instruction book, it’s yours to write. You’ll figure it out, ship it, and iterate.

What do we expect from you? 🙌🏻

• 3-6 years of relevant work experience in a Data Engineering role.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimising data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Good understanding of Airflow, Spark, NoSql databases, Kakfa is nice to have.

Interested? Here's how you can reach us 📲

✉️ [email protected]