Senior Data Engineer
Rea Group
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Job summary
Oolio, an Australian-based start-up, seeks a Senior Data Engineer to design, build and optimise data pipelines and platforms. You will work with the data team to ensure robust ETL/ELT processes, governance, and scalable analytics solutions across cloud environments. Hybrid/remote work options available.
You will lead data modelling, warehousing, and BI reporting using FineReport and FineBI, collaborating with IT and business stakeholders to unlock insights and drive decisions.
Qualifications
- Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related discipline.
Responsibilities
- Design and develop scalable batch and real-time data pipelines on GCP/AWS/Azure environments.
- Build robust ETL/ELT solutions to ingest, transform and model data from multiple sources.
- Create data models and data warehouse architectures to support reporting and analytics.
- Develop and deliver complex reports and dashboards using FineReport and FineBI.
- Collaborate with stakeholders and cross-functional teams; mentor engineers and promote best practices.
- Implement CI/CD and Infrastructure as Code for data platforms; document procedures.
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BYD is a high-tech company devoted to technological innovations for a better life. BYD is dedicated to providing zero-emission energy solutions.
As a leading battery-electric zero-emission vehicle (ZEV) manufacturer, BYD has created a broad range of battery-electric, hybrid-electric, and internal combustion (IC) passenger vehicles. Developing electric vehicles that are intelligent and connected, BYD is inaugurating a new age of automotive innovation featuring a sleek design and an innovative user experience.
About the Role
Based at BYD’s Mulgrave office, this role will be part of our Headquarters Digital Solution Centre and work closely with the local IT team. This is a fixed-term contract position with the potential to transition to a permanent role.
The position will be responsible for the development and optimisation of BYD’s big data platforms, data warehouse and BI solutions. This includes designing and implementing ETL processes, developing data models and data warehouse architectures, and delivering business reports, dashboards and data visualisations using FineReport and FineBI.
The role will work closely with business and IT teams to support data analysis, identify business insights, and deliver reliable and scalable data solutions that support business decision-making.
Key Responsibilities
Develop and optimise big data platforms, including designing and implementing ETL processes for data extraction, cleansing, transformation and loading.
Design and develop data warehouse models and architectures to support business reporting and analysis.
Develop and deliver complex reports, dashboards and data visualisations using FineReport and FineBI.
Participate in big data application development and perform data analysis and mining based on business requirements.
Optimise data storage and processing performance to improve system efficiency, stability and scalability.
Key Requirements
Bachelor’s degree or diploma in Computer Science, Software Engineering, Data Science, Information Systems, or a related discipline. Equivalent relevant industry experience will also be considered.
Minimum 3 years of experience in big data development, data engineering or BI, with experience working on end-to-end data projects.
Strong knowledge of big data technologies such as Hadoop, Spark, Hive or HBase, with experience in large-scale data processing.
Strong SQL skills and experience with relational databases such as Oracle, MySQL or SQL Server, including SQL performance tuning.
Good understanding of data warehousing, data modelling, ETL development and OLAP analysis.
Hands-on experience with FineReport and/or FineBI, with experience delivering reporting or BI projects from requirements through to implementation.
Strong analytical and problem-solving skills, with the ability to understand business requirements, communicate with stakeholders and produce clear technical documentation.
Strong communication and teamwork skills, with the ability to work effectively with local and overseas IT teams.
Experience in data warehouse development, user profiling or AI-related data applications is an advantage.
PR/VISA STATUS of Applicant: Citizen or Holding a Valid PR. Please do not apply if you need sponsorship.
Oolio is an Australian-based start-up on a mission to empower the hospitality industry. Our platform is built with the sole purpose to assist venues to do what they do best – Provide an exceptional experience to their patrons during moments that matter. Whilst this platform is new, we are part of an established international group of successful companies thus giving you the freedom of a start-up with the support of an experienced group of leaders and backed by one of Australia’s leading investment funds.
Our Data team manage and maintain all the data streams incoming into our warehouse with proper data orchestration pipelines (ETL/ELT)and ensure the consumers are provided with the access to the data they are interested in.
Starts with data extraction from different sources, continuing with the loading and transformation of these data, all the way to the creation of reports and other data products
- Designing, coding, testing, and deploying new data management tools and systems.
- Create data pipelines between various source systems such as Hubspot, Netsuite, POS to Lake/Warehouse
- Data wrangling– getting our data into the right shape for answering questions and building models takes skill, and may require use of big-data technologies
- Write queries and develop pipelines to surface data analysis and visualisations for internal and external users
- Degree in Mathematics/Statistics, Computer Science or IT
- Min 5+ years’ experience in data engineering
- Proficient python skills that can be used for both ad hoc analysis and for building maintainable and efficient data pipelines
- Advanced SQL skills
- Experience in R/Spark is a plus
- Experience with BI tools such as PowerBI, Tableau
- Exposure to Snowflake and Airflow
- Exposure to ML models
- Experience with DevOps practices and techniques, such as Docker and CI/CD tools.
- Exposure to data engineering concepts and associated technologies such as Airflow/Fivetran, BigQuery Kafka, batch and real-time data pipelines, ELT, and SQL.
- Exposure to unstructured and structured data
The Senior Data Engineer is responsible for the design, development, testing, maintenance, and documentation of data pipelines and data platforms in accordance with client requirements, system specifications, and defined technical architecture.
The role undertakes analysis of system requirements and evaluates existing data systems, identifying limitations and deficiencies in processes and methods. The position is accountable for the full lifecycle of data solutions, including requirements gathering, design, implementation, testing, deployment, and ongoing production support.
The Senior Data Engineer is responsible for the design, development, testing, maintenance, and documentation of data pipelines and data platforms in accordance with client requirements, system specifications, and defined technical architecture.
The role undertakes analysis of system requirements and evaluates existing data systems, identifying limitations and deficiencies in processes and methods. The position is accountable for the full lifecycle of data solutions, including requirements gathering, design, implementation, testing, deployment, and ongoing production support.
- Data Architecture & Design Analyse and evaluate client data system requirements Design data architectures, including Lakehouse and medallion patterns Define data models, schema structures, partitioning strategies, and storage layouts Develop solutions primarily using Databricks within AWS, Azure, and GCP environments
- Data Pipeline Development Design, develop, and maintain data pipeline code using Python, Scala, and SQL Implement data ingestion, transformation, and delivery processes in accordance with system specifications Test, debug, and resolve defects in line with established standards and protocols Utilise AI development tooling such as Genie Code, Copilot or Claude
- Data Quality & Governance Develop and implement data quality frameworks, validation processes, and monitoring mechanisms Ensure data platforms operate in accordance with defined specifications and governance requirements Prepare and maintain technical documentation and operational procedures
- Infrastructure & Platform Engineering Develop and manage infrastructure using Infrastructure as Code tools (e.g. Terraform, CDK, CloudFormation) Maintain version-controlled infrastructure definitions Support CI/CD processes for automated deployment of data systems Design and implement integrations with enterprise systems, including identity, security, and compliance frameworks
- System Integration and Improvement Identify and assess limitations in existing systems and platforms Design and implement solutions to address integration, performance, and scalability requirements
- Technical Strategy & Advisory Provide technical input into data system design, platform selection, and architecture decisions Contribute to the development of proposals, including cost estimation and financial evaluation of technology options
- Client Enablement and Knowledge Transfer Work collaboratively with client teams to support implementation and operation of data platforms Develop and maintain documentation to support ongoing system use and maintenance Facilitate knowledge transfer to enable client self-sufficiency
The role operates across multi-cloud environments and requires the design of data systems that are portable and scalable. Platforms include:
- AWS: Databricks, S3, Glue, Lambda, EventBridge, Redshift, IAM, VPC, KMS
- Azure: Databricks, ADLS Gen2, Synapse, Data Factory, Event Hubs, Key Vault, Entra ID, ExpressRoute
- GCP: Databricks, GCS, BigQuery, Dataflow, Pub/Sub, IAM
- Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related discipline
- OR at least 5 years’ relevant professional experience with appropriate vendor certifications
- Databricks Data Engineer Associate and/or Data Engineer Professional certification
- Experience with Databricks in a production environment, including Delta Lake and UnityCatalog
- Proficiency in SQL and Python or Scala
- Experience in designing and implementing data quality and validation frameworks
- Demonstrated ability to communicate technical concepts clearly to non-technical stakeholders
- Strong software engineering practices, including testing, version control (Git), and CI/CD
- Experience with Infrastructure as Code tools (e.g. Terraform, CloudFormation)
- Understanding of distributed systems and data pipeline design
- Ability to produce clear and comprehensive technical documentation
- Demonstrated experience delivering and maintaining production data systems
- Experience with real-time or streaming data systems (e.g. Kafka)
- Knowledge of data governance, privacy, and compliance frameworks (e.g. APRA CPG234, ISO 27001, CIS Benchmarks)
- Machine learning infrastructure and pipelines (on Databricks or cloud platform)
- Background in platform engineering or Site Reliability Engineering
- Cloud platform certifications (AWS, Azure, or GCP)
- Experience contributing to technical knowledge sharing or capability development within teams
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About the Client This clientis a leading Australian wealth management company that provides superannuation, financial advice, and asset management services. the company traces its origins back to 1846.
About the Role We are seeking an experienced Senior Data Engineer to join a high-performing Data Engineering team delivering enterprise-scale data solutions on Google Cloud Platform (GCP). This is a hands-on engineering role where you'll design, build and optimise modern data pipelines that enable trusted, scalable data for reporting, analytics and business decision-making. Working closely with Solution Designers, Data Architects and cross-functional technology teams, you'll play a key role in delivering robust batch and real-time data solutions while driving engineering best practices, mentoring team members and contributing to the continuous improvement of the data platform.
Required Experience Design, develop and maintain scalable batch and real-time data pipelines on Google Cloud Platform (GCP). Build robust ETL/ELT solutions to ingest, integrate, transform and model data from multiple enterprise source systems. Collaborate with stakeholders to deliver data solutions aligned to business and technical requirements. Develop high-quality, production-ready code using modern software engineering practices. Optimise data pipelines for performance, scalability, reliability and cost efficiency. Implement automated testing, monitoring and CI/CD practices to support reliable production deployments. Conduct code reviews and provide guidance to engineers. Troubleshoot production issues, perform root cause analysis and implement long-term improvements. Champion engineering standards, reusable frameworks and continuous improvement initiatives across the data engineering function. Work collaboratively within Agile delivery teams and contribute to sprint planning, estimation and technical design discussions.
About You You'll be a passionate Data Engineer who enjoys solving complex engineering problems while delivering reliable, scalable data solutions within enterprise environments.
You'll bring 10+ years’ experience in Data Engineering, Software Engineering or ETL Development. Strong commercial experience delivering enterprise data solutions on Google Cloud Platform (GCP). Expertise with BigQuery , Dataflow, Cloud Composer (Airflow), Pub/Sub and Cloud Storage. Advanced SQL skills and strong programming experience with Python (Java or Scala also beneficial). Strong understanding of ETL/ELT frameworks, data integration and modern data engineering principles. Experience designing dimensional data models and enterprise data warehouse solutions. Hands-on experience with CI/CD pipelines, Git, Infrastructure as Code (Terraform preferred) and automated testing. Strong understanding of data quality, metadata management, monitoring and observability. Experience tuning data pipelines for performance, scalability and reliability. Excellent stakeholder engagement and communication skills, with the ability to work across Architecture, Security, Infrastructure and business teams. Previous experience mentoring engineers and performing technical code reviews.
Opportunity to work on a large-scale enterprise cloud data platform. Modern GCP technology stack and engineering-led environment. Collaborative, high-performing team with strong technical leadership. Exposure to enterprise architecture, cloud transformation and modern data engineering practices. Flexible working arrangements with hybrid/remote options.
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