Introduction:
Worley is a global professional services company of energy, chemicals and resources experts headquartered in Australia. Right now, we’re bridging two worlds as we accelerate to more sustainable energy sources, while helping our customers provide the energy, chemicals and resources that society needs now.
We partner with our customers to deliver projects and create value over the life of their portfolio of assets. We solve complex problems by finding integrated data-centric solutions from the first stages of consulting and engineering to installation and commissioning, to the last stages of decommissioning and remediation.
Data Engineer
Benefits: Flexible Working, Remote Working, Pension, Extra Holiday Purchase Scheme, & Many More.
Role Context:
Design, build, and maintain the infrastructure and systems that allow the UIS Data Science team to collect, store, process, and analyse large amounts of data. Design and implement data pipelines, integrating data from various sources, and ensure the data is accurate, complete, and accessible to those who need it. You will work as part of the Customer Solutions team which, in turn, is part of the Growth Division of Worley.
Team:
You will work in the Unconventional Industrial Solutions team which sits in the wider Customer Solutions team is part of Worley’s Growth Division. Our team of consultants, technology experts, data scientists, developers and engineers support our customers as they embrace digital technology and transform their organization. We complement conventional engineering approaches to solving problems, by leveraging subject matter expertise and domain knowledge alongside simulation-driven design, data science and machine learning.
Our mission is to make energy affordable and accessible to everyone - enabled by providing our clients with 5 key capabilities:
1.Digital Advisory services & Human-Centric Service Design
2.End-to-End Digital Twins as a foundation for smart advisory
3.Take advisory services & breakthrough analytics solutions to the next level by productizing them and serving them to our clients & ecosystem through user centric B2B marketplace
4.Sustainability solutions
5.Autonomous solutions design and implementation
You'll be:
The day-to-day responsibilities of the data engineer will vary depending on the specific project being worked on but will typically include:
·Collaborating with data scientists, analysts, front end developers and other stakeholders to understand and meet their data needs.
·Designing, building, and maintaining the data infrastructure and pipelines that support data-driven applications and analytics.
·Managing and monitoring data pipeline performance and troubleshooting any issues that arise.
·Work with a wide variety of data types and sources including structure, unstructured, semi-structured and sensor data
·Optimising and scaling data storage and processing systems.
·Ensuring data quality and consistency across different systems and platforms.
·Developing and implementing data security and privacy controls.
·Quickly build prototypes and proofs-of-concept to prove value of propostions
·Collaborating with other teams in Customer Solutions and Worley: Working with other teams within the organisation, such as Solutions Factory (DevOps and data systems), PMO, and project teams. Understand customers’ challenges, agree and deploy solutions.
·Management: coaching and line-management responsibilities subject to experience and team structure
You'll have:
Technical
·Demonstrate deep understanding of the complexities and nuances of structured and unstructured industrial data, and how to prepare it for analysis
·Make full use of technology to automate data pipelines and build analytical warehouses
·Deep understanding of cloud-based data platforms (Azure SQL DB, Azure Synapse, ADLS, AWS, Hadoop, Spark, Snowflake, No-SQL etc).
·Proficient scripting in programming languages such as Java, Python, Scala
·Expert in SQL
Machine Learning
·Good basic understanding of the main types of ML model with particular reference to the required data structures, formats and hygiene.
·Au fair with how current machine learning tools and platforms (Python, IBM, Knime, Github, R, Spark, Weka, Amazon ML, Azure ML etc) integrate as part of the analytical ecosystem
·Experience with the tools used to validate, monitor and deploy ML models (Tensorflow, ML Flow, AWS Studio, Docker, Kubernetes etc).
Applied Analysis and Insight
·Understand enterprise-wide business-processes, IT systems and data
·Designs data flows and platforms that enable businesses to execute long term data strategy
·Work with data scientists and data owners throughout a project to ensure data is interpreted correctly and solutions are viable
·Experience in processing of IOT/Sensor Data to solve problems in an industrial setting
Softer Skills
·Build relationships with key technical and senior stakeholders across the business
·Spend time with customers to fully understand the challenges and the nuances of their organisation and data.
·Be comfortable working in Agile project-management frameworks.
Analytical Knowledge
·Ensures that analysts have ready access to clean, accurate and properly-documented data
·Able to interrogate data to understand its quality and distribution, informing required transformations
Moving Forward:
We want our people to be energized and empowered to drive sustainable impact. So, our focus is on a values-inspired culture that unlocks brilliance through belonging, connection and innovation.
We’re building a diverse, inclusive and respectful workplace. Creating a space where everyone feels they belong, can be themselves, and are heard. And we're not just talking about it; we're doing it. We're reskilling our people, leveraging transferable skills, and supporting the transition of our workforce to become experts in today's low carbon energy infrastructure and technology.
Whatever your ambition, there’s a path for you here. And there’s no barrier to your potential career success. Join us to broaden your horizons, explore diverse opportunities, and be part of delivering sustainable change.