Who we are

Founded in 2016, Lusha grew from a bootstrapped startup to a $1.5B unicorn, backed by $245M in investments and trusted by sales teams at Google, Zendesk, and Yotpo.

Lusha is changing the B2B sales experience with a new approach called Sales Streaming. It allows salespeople to search for any lead in the world, then our AI finds them better ones, keeps them streaming and does outreach for them. This means they can now spend most of their time actually selling.

With 1.5M+ users, 200M+ contacts, and 40K new signups every month, we’re the engine behind modern GTM teams. And we’re just getting started.

Where does this role fit in our vision?

At Lusha, data is everything—it’s at the heart of every product decision, every customer insight, and every strategic move we make. The Data Group builds and maintains the core data assets that power our products, from our Company and Contact databases to our Connect and Recommendation systems. This role sits at the forefront of that mission, leading engineering innovation that directly shapes the experience of our growing user base and drives the evolution of Lusha’s intelligent data services.

What will you be responsible for?

• Lead the design and development of scalable, high-performance data workflows, including both batch pipelines and real-time data products.
• Define, implement, and enforce engineering best practices related to code quality, testing, CI/CD pipelines, observability, and documentation.
• Mentor, support, and grow a team of data engineers, fostering a collaborative and high-performance engineering culture.
• Identify opportunities to create new data assets and features that expand Lusha’s product capabilities and value proposition.
• Drive architectural decision-making in areas of data modeling, storage solutions, and compute resources within cloud environments such as Databricks and Snowflake.
• Collaborate closely with cross-functional stakeholders—including Product, DevOps, and R&D—to ensure effective delivery and platform stability.
• Promote and champion a data-driven mindset across the organization, balancing technical rigor with business context and strategic goals.