Job Description
Data Architecture Melbourne Australia Regular / Full time
n
Description
n
About the Role
n
Vericent is partnering with a leading global technology consulting organisation to recruit an experienced Data Engineer. This is an exciting opportunity to work on enterprise-scale data initiatives, building up-to-date data pipelines and cloud-based data solutions that enable analytics, reporting, and AI-driven outcomes.
n
In this role, you'll collaborate with cross-functional teams, including data scientists, software engineers, product owners, and business stakeholders, to design, develop, and optimise scalable data integration and transformation solutions. You'll also play a key role in ensuring data quality, reliability, security, and performance across the entire data lifecycle.
n
Key Responsibilities
n
n
Design, build and maintain batch and near-real-time data pipelines.
n
Develop ingestion and transformation processes for structured and semi-structured data.
n
Build reusable data components and curated datasets for reporting, analytics and machine learning.
n
Develop solutions using SQL, Python, dbt, PySpark or equivalent technologies.
n
Integrate data from enterprise applications, APIs, event streams and external sources.
n
Optimise data pipelines for reliability, performance and cost.
n
Support migration and modernisation of legacy data processes.
n
n
Data Modelling and Quality
n
n
Develop logical and physical data models aligned to business requirements.
n
Build dimensional, relational and analytical data structures.
n
Implement data-quality rules, reconciliations and validation controls.
n
Investigate data defects and coordinate remediation with source-system and product teams.
n
Maintain data definitions, lineage,



metadata and technical documentation.
n
Apply appropriate handling for sensitive, customer and commercially restricted data.
n
n
Engineering and DevOps Practices
n
n
Develop maintainable, tested and version-controlled data solutions.
n
Implement automated testing across ingestion, transformation and data-quality processes.
n
Support CI/CD pipelines and controlled deployment across development, test and production.
n
Participate in code reviews and apply engineering standards.
n
Implement monitoring, alerting and operational logging.
n
Reduce manual deployment and support activities through automation.
n
n
Production Support and Operations
n
n
Monitor production pipelines, schedules and data-processing workloads.
n
Investigate and resolve failed jobs, delayed data and data-quality incidents.
n
Participate in incident, problem and change-management processes.
n
Perform root-cause analysis and implement permanent remediation.
n
Maintain operational runbooks, support procedures and recovery steps.
n
Work with Platform Operations to ensure data products meet availability and service-level requirements.
n
n
Collaboration and Delivery
n
n
Work with product owners and stakeholders to define data requirements and acceptance criteria.
n
Collaborate with data scientists to provide model-ready datasets and features.
n




Work with software engineers to support application and API data requirements.
n
Contribute to technical design, estimation and delivery planning.
n
Communicate data risks, dependencies and design decisions clearly.
n
n
Required Skills and Experience
n
n
Advanced SQL skills and strong understanding of data structures and query performance.
n
Experience with at least two of the following:
n
Snowflake
n
dbt
n
Databricks and PySpark
n
Experience building automated data-ingestion and transformation pipelines.
n
Strong understanding of data modelling, warehousing and analytical data patterns.
n
Experience implementing data-quality controls and reconciliation processes.
n
Experience with Git, code reviews and CI/CD practices.
n
Understanding of cloud security, access control and data-protection requirements.
n
Experience supporting production data pipelines and resolving operational incidents.
n
Strong technical documentation and stakeholder-communication skills.
n
Tertiary qualification in computer science, engineering, information systems or a related discipline, or equivalent practical experience.
n
n
Key Deliverables and Success Measures
n
n
Reliable and scalable data pipelines and data products.
n
Achievement of agreed data availability and processing service levels.
n
Reduction in pipeline failures and recurring data-quality issues.
n
Accurate, traceable and well-documented datasets.
n
Automated testing, deployment, monitoring and recovery processes.
n
Improved pipeline performance and cloud-cost efficiency.
n
Compliance with security, data-governance and engineering standards.
n
Positive engagement with product, platform, analytics and business stakeholders.
n
#J-*****-Ljbffr

📌 Data Engineer (Victoria)
🏢 Vericent Pty
📍 Victoria