Staff Data Engineer
Latitude Financial Services Melbourne, Victoria, Australia
Financial Services · 501-1,000 employees
About the role
The Staff Data Engineer leads the end-to-end technical delivery of data platforms and pipelines while providing guidance to local and offshore engineering teams. This role is responsible for maintaining operational reliability, enforcing engineering standards, and collaborating with cross-functional teams to ensure secure and scalable data solutions.
What they look for
Requirements
Candidates must have a bachelor's degree in computer science or a related field and at least 7 years of experience in data engineering. Strong hands-on expertise with cloud platforms like Snowflake and AWS, along with proficiency in Python, SQL, and modern data orchestration tools, is required.
Benefits
Full description
The Staff Data Engineer is the hands-on technical authority for the team's day-to-day data engineering delivery and operations. Reporting to the Principal Data Engineer, this role owns the day-to-day technical decisions, quality and reliability of data platforms and pipelines in-flight, and is the primary escalation point for the engineering team on technical and operational matters.
The Staff Data Engineer is accountable for supporting the principal engineer with solution architecture and designs, translating these into consistent day-to-day execution, patterns and for continuously improving how the team runs data operations.
The role works closely with local and offshore engineers, architects, security teams and platform teams to ensure data solutions are reliable, interoperable, and aligned with Latitude’s broader data and cloud strategy. The staff data engineer will provide technical guidance to engineers, resolve complex operational and delivery challenges, and contribute directly to solution design, development, testing, and implementation.
In this role, you’ll:
- Lead technical delivery: Lead the end-to-end engineering delivery of data platforms, pipelines and data products, ensuring solutions meet agreed functional and non-functional requirements and comply with the LFS data engineering standards.
- Engineer scalable data solutions: Translate architectural direction established by the Principal Data Engineer and enterprise architecture teams into practical, scalable and secure solution designs using platforms such as Snowflake, Airflow, AWS and other agentic and data development frameworks.
- Remain hands-on: Contribute directly to solution development, code reviews, testing, troubleshooting, deployment and production support as part of a local and offshore engineering team.
- Drive engineering excellence: Own engineering standards in practice: Enforce and uphold the team's CI/CD, automated testing, code quality, observability and DevSecOps standards day to day through code reviews, definition-of-done gates and hands-on remediation, ensuring standards set by the Principal Engineer are consistently applied across every delivery."
- Support platform interoperability: Build solutions that enable secure and seamless data movement, integration and collaboration across platforms, business domains and engineering teams.
- Guide engineering teams: Provide day-to-day technical direction: Act as the go-to technical decision-maker for local and offshore engineers on delivery and operational questions, allocating and unblocking work, reviewing designs and code, and coaching engineers through complex problems in-flight.
- Maintain operational reliability: Own operational reliability day to day: Act as the technical owner for the run-state of data pipelines and platforms — triaging incidents, leading root-cause analysis, meeting SLAs/SLOs, and driving the fixes, observability and automation that reduce recurring operational toil week to week.
- Embed governance and security: Work with data governance, cyber security and privacy teams to incorporate metadata management, data lineage, data quality, access controls and regulatory requirements into solutions by design.
- Support strategic initiatives: Partner with the Principal Data Engineer and other technical leaders to support strategic data and cloud transformation initiatives, including platform modernization and migration programs.
- Manage technical risks and dependencies: owning day-to-day delivery and operational risks and dependencies directly and escalating significant architectural or enterprise-standard-setting decisions to the Principal Data Engineer.
- Agentic development: Help shape what agentic development frameworks and harness kits that help teams accelerate consistency, quality and output in our development lifecycle, and importantly support the adoption across teams contributing to our data systems and platforms.
What you’ll bring:
- You are familiar with AI tools - comfortable using tools to accelerate insights, automate routine work, prepare reporting, and tailor content quickly and effectively. (for individual contributor roles)
- AI-native - regularly leverages AI tools to enhance decision-making, automate reporting, accelerate content creation, and drive greater efficiency across your team (for people leader roles)
- ·Bachelor’s degree in computer science or information technology or a related discipline.
- ·7+ years of experience in data engineering, including experience leading the technical delivery of complex data solutions.
- ·Strong hands-on experience with cloud data platforms and services - Snowflake and AWS.
- Demonstrated experience designing and building scalable data pipelines using modern technologies such as dbt, Airflow, Kafka, Spark
- ·Strong programming and automation experience using technologies such as Python, SQL, Terraform and CloudFormation.
- Strong experience and practices with best practice AI assisted development, in particular leveraging harnesses, kits and agentic development frameworks.
- Experience implementing CI/CD pipelines, automated testing, monitoring, observability and DevSecOps practices for data platforms.
- Experience applying Infrastructure as Code and automation-first principles to the development and operation of data platforms.
- Experience designing or contributing to self-service data platforms and reusable engineering frameworks.
- Strong understanding of data integration patterns, pipeline orchestration, and distributed data processing.
- Proven ability to build data solutions with strong performance, scalability, security, maintainability, and reliability characteristics.
- Understanding of data governance, metadata management, lineage, data quality, security, privacy and access-control principles.
- Experience leading technical delivery across local and offshore or distributed engineering teams.
- Experience coaching and mentoring junior and mid-level engineers. Inclusive of the ability to conduct design or code review and support other engineers in troubleshooting complex technical issues and helping them make pragmatic engineering choices.
- Strong stakeholder engagement, collaboration, and communication skills, with the ability to explain complex technical topics clearly.
- A continuous-improvement mindset and willingness to learn, experiment and challenge established technologies and practices constructively.
- Ability to balance hands-on delivery with technical operational leadership, team support, and longer-term platform objectives.
Sometimes the best candidates don’t have 100% of what is listed above, but if you have most and are confident, you’d be a good fit, we’d love to hear from you!
Sound like you? That's a good sign! In return for your energy and ideas, we offer a flexible working environment and great compensation. We always support a safe, healthy, engaging, and productive working environment for all employees and workers, whether that be in your home and office, or a combination of both.
We make it possible – for our customers, our partners, and our people.
We believe doing great work starts with feeling supported. Our values, take ownership, pursue excellence, win together, and create tomorrow, aren't just words. They show up in how we work, how we lead, and how we look after our team.
We make it possible…
- to spend more time with your loved ones – with an extra week of paid leave each year through our Take 5 initiative.
- to balance work and life – with a hybrid working model, giving you the flexibility to work from home while connecting in the office.
- to put your wellbeing first – with Sonder, a 24/7 support app for mental and physical wellness.
- to access great financial benefits – with discounts on Latitude products and services.
When our people thrive, everything else follows.
Successful applicants will be required to complete a background check (including criminal history and bankruptcy check) prior to commencement of employment.
Similar roles
-
Senior AI & Data Engineer (m/w/d)
Highberg Hamburg, New York, United States
-
AI & Data Engineer (m/w/d)
Highberg Hamburg, New York, United States
-
Data Engineer & BI Analyst
Paradigma Digital - Nuestras ofertas de Empleo Pozuelo de Alarcón, Community of Madrid, Spain
-
Senior Data Engineer
Cohere Health Hyderabad, Telangana, India
-
Senior Data Engineer (Databricks, MLOps, AWS)
GoTymeX Hà Nội, Vietnam
-
Data Engineer - INSIGHTS
STOW Group Lokeren, East Flanders, Belgium