Data Engineer

About the Role
We are seeking an experienced, energetic, and highly motivated Data Engineer to join our dynamic organisation as part of our Data and AI practice within the Data Engineering Team. You will be a lead part of a team of Data and AI practitioners delivering amazing technical solutions to our customers and our own business. This position demands a high level of expertise in Data Engineering technologies, particularly across the Google Cloud Platform (GCP) data stack and open-source big data ecosystems, a deep understanding of business contexts, and a strong motivation to innovate and lead. This is an environment where you can bring your energy and ideas, and we help you translate them into tangible solutions that drive real value.

Responsibilities
The successful candidate will be expected to deliver excellence across three core pillars:

• Technical Mastery and Execution: Bring a wealth of experience in architecting and building robust, scalable batch and real-time streaming pipelines. Possess deep understanding of cloud-native data ecosystems, open-source big data specifications, and distributed computing, while also staying at the forefront of GenAI technologies to solve complex, modern problems.
• Project Leadership and Delivery: Take leading roles in project delivery, ensuring that technical solutions are executed successfully from concept to production. Drive accountability, manage complex technical timelines, and ensure high-quality outcomes that align with our clients' strategic goals.
• Business Acumen and Initiative: Go beyond the code to deeply understand the underlying business challenges our customers face and translate complex technical architectures into business value. Be proactive in identifying opportunities to improve our services, architectures, or internal systems.
• Mentorship and Skills Development: Refine your own skills and mentor junior engineers, guide technical discussions, lead the development of Proof of Concepts (POCs), and elevate the overall capability of our Data practice.

What You Can Expect From Us

• Technology Stack: Adapt to what our customers need, focusing on a robust set of data engineering technologies, primarily centered around the Google Cloud Platform (GCP), including BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, and Cloud Composer, combined with core open-source big data technologies like Apache Spark, Hadoop, Python, and SQL. We are also exploring Generative AI frameworks.
• A Platform for Impact: A supportive environment that values your senior expertise from day one, providing the space and resources to architect innovative data solutions, lead complex projects, and make a direct impact on our customers' success in a forward-deployed environment.
• A Culture that Values Your Journey: We believe in autonomy, mastery, and purpose, trusting you to bring your best self and pursue continuous growth. We provide interesting and challenging work within a collaborative organisation where colleagues support each other, brainstorm together, and build together.

Requirements

• At least 7 years of proven industry experience in data engineering, data architecture, and enterprise software systems.
• A Computer Science (or equivalent) degree, or equivalent practical experience.
• Deep expertise in modern cloud architectures and GCP data engineering services (e.g., BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, Cloud Composer, Dataplex) for designing resilient batch and streaming pipelines.
• Exceptional, hands-on proficiency in core Data Engineering technologies, specifically Python, SQL, and Apache Spark, as well as key Data Management concepts.
• Deep understanding of diverse data architectures, such as open-source Big Data ecosystems, Hadoop, distributed computing, cloud-native databases, enterprise data lakehouses, and advanced analytics.
• A strong foundational grasp of both traditional data engineering paradigms and modern Generative AI (GenAI) technologies.