Engineering Lead
11 hours ago
Engineering LeadASX-Listed FinTech, Sydney Hybrid
Up to $200k + Super + Bonus + LTVI
Overview:We are looking for a highly capable Engineering Lead to guide and scale a high-performing Data & Machine Learning Engineering team (5–6 engineers). You must also come from a Software Engineering background.
This role blends technical leadership (50%) with hands-on engineering (50%), driving the build of scalable data platforms, ML infrastructure, and API-driven services that power real-time financial products.
You'll work closely with Product, Data Science, Platform, and broader Engineering to deliver high-quality solutions in a fast-moving FinTech environment.
Key Responsibilities Leadership & Delivery
- Lead, mentor and develop a team of 5–6 Data & ML Engineers (mid, senior and principal levels).
- Own engineering delivery across data pipelines, ML systems, API services and platform tooling.
- Set best practices for coding, design, testing, observability, and deployment.
- Drive architectural decisions and ensure scalable, reliable engineering outcomes.
- Collaborate with Product, Data Science and business stakeholders to define roadmaps and translate requirements into actionable technical work.
- Foster a culture of ownership, learning, high performance and cross-functional collaboration.
Hands-On Engineering (50%)
- Build, optimise and deploy data and ML pipelines using Python, AWS, Databricks, and modern orchestration tooling.
- Contribute to core API development using Python, Golang or Java.
- Participate in code reviews, systems design, and complex technical problem solving.
- Build reusable frameworks enabling data scientists to train, deploy and monitor models at scale.
- Improve reliability, latency and throughput of online inference systems.
Core Technical Stack
- Languages: Python (primary), Golang or Java or similar accepted if not Python.
- Cloud: AWS (Lambda, ECS/Fargate, API Gateway, S3, Step Functions, EMR, etc.)
- Data Platform: Databricks, Spark, Delta Lake.
- MLOps / Infra: MLflow, Docker, CI/CD, Feature Stores, observability tooling.
- APIs: RESTful APIs, microservices, real-time data ingestion & online inference.
What We're Looking For Essential
- 7+ years in software/data/ML engineering roles with strong hands-on coding ability.
- Proven experience leading engineering teams (formal or informal).
- Strong background in backend/API engineering with Python, Golang, or Java.
- Deep experience building scalable data systems, distributed processing, and productionised ML workflows.
- Strong understanding of cloud-native architectures (AWS preferred).
- Experience working cross-functionally with Data Science, Product and Platform teams.
- Excellent communication, stakeholder management and technical leadership skills.
Nice to Have
- Experience in FinTech, lending, payments, or high-throughput consumer platforms.
- Previous work on online inference, real-time ML, or event-driven architectures.
- Exposure to security, compliance or responsible AI considerations.
Why This Role Is Exciting
- Lead and scale the engineering capability behind a rapidly growing real-time FinTech product.
- Build next-generation data & ML systems, including online inference and personalised decisioning.
- Influence architecture, hiring and long-term technology strategy.
- Plenty of room for innovation, autonomy and making a measurable business impact.
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