A complete application in a minute — tailored resume and cover letter, ready to send.
Preacta is modernizing its data platform, migrating core data warehousing to Databricks, and moving reporting away from legacy BI tools. You will lead a distributed analytics team, drive delivery, and shape architecture while balancing cost and performance.
The role requires hands-on data engineering leadership and strong stakeholder management across time zones. You will partner with the Lead Data Engineer to guide technical direction, oversee sprint planning, and grow the team with clear
A fast-growing, product-led SaaS business with customers across dozens of countries, built on a collaborative cloud platform and supported by a distributed, global team. It's a business that's scaled fast and now needs strong engineering leadership to match, with genuine investment in its people and a track record of promoting from within.
The business is mid-way through a significant modernisation of its data platform, moving core data warehousing onto Databricks and shifting reporting away from its legacy BI tool. The architecture is largely in place and the team has done solid work stabilising it, but there's a real program of work ahead to take it through to full production maturity. That's what this role owns.
This isn't a purely people-management seat. You'll need enough depth in modern data platforms and architecture to challenge technical direction and work closely with the Lead Data Engineer, but your core value will be driving delivery, building the team, and managing the trade-offs between performance, infrastructure cost and business outcomes.
Day to day, you'll create clear structure around priorities, timelines and deliverables, run a healthy Scrum cadence with product and design, and work to improve data refresh times with real-time as a longer-term goal. You'll also improve collaboration between product engineering and analytics so product changes don't break downstream reporting, and you'll coach and grow your engineers with clear expectations and regular feedback.
You'll inherit an established, distributed data engineering and analytics team, with real scope to shape how it grows from here, including making the call on where further hiring is genuinely needed.