Engineering Manager - Data & Analytics

Preacta; Sydney; On-site; AUD 180,000 - 280,000; Full time

Job summary

Preacta, a fast-growing SaaS company, is modernising its data platform by migrating data warehousing to Databricks and transitioning away from legacy BI tooling. This role owns the program to push the architecture through production maturity while guiding delivery.

You will lead the distributed data engineering and analytics team, shaping hiring, setting priorities, and balancing performance, cost, and business outcomes.

Qualifications

• Significant experience leading data/analytics teams
• Proven track record delivering data platform migrations
• Strong understanding of distributed systems and data integrity
• Experience with Databricks and cloud data warehousing
• Ability to balance performance, cost and business outcomes

Responsibilities

• Own delivery program and team growth for the data platform
• Set priorities, timelines and deliverables; run Scrum with product and design
• Mentor engineers and provide clear feedback
• Collaborate with analytics to safeguard downstream reporting

Skills

Engineering leadership

Team management

Data architecture

Databricks

Scrum/Agile

Multi-cloud data warehousing

Tools

Databricks

Cloud platforms

Job description

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.

Role and responsibilities

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.

Key technical skills

• Came up as a senior individual contributor, likely in data or analytics engineering, before stepping into management
• Two-plus years leading engineering teams, with a track record of improving speed and quality through better process and technical decisions
• Solid grounding in distributed systems and data integrity at scale, enough to hold your own on architecture and platform calls
• Hands-on experience running large, multi-cloud data warehouse migrations while keeping an eye on infrastructure cost
• Confident running sprint planning and delivery alongside product and tech leads, juggling new features against bugs, enhancements and maintenance
• A strong track record on stakeholder management and delivery, bonus points if you've steered a troubled program back on course
• Comfortable communicating clear across different locations and time zones