• Advanced GCP Data Engineering Expertise :Robust hands -on experience with GCP services such as BigQuery, Dataflow, Pub/Sub, Dataproc, and Cloud Storage for building large -scale data platforms.
• Data Architecture &Modeling;:Deep understanding of data warehousing, dimensional modeling, and lakehouse architectures to support analytics and reporting.
• Leadership& Stakeholder Collaboration:Proven ability to lead engineering initiatives, mentor teams, and collaborate with business, analytics, and architecture stakeholders to deliver data solutions.
• ExpertiseScalable Data Pipeline Development:Expertise in designing and implementing high -performance ETL/ELT pipelines (batch and real -time) using Python, SQL, and frameworks like Apache Beam or Spark.
Nice to Have Skills:
• Experience with Containerization &Kubernetes;:Experience with Docker and Kubernetes (GKE) for deploying and managing scalable data platforms.
• Knowledge of Streaming & Real -Time Processing:Familiarity with Kafka, Pub/Sub streaming, and event -driven architectures for real -time data processing.
• Multi -Cloud Experience:Exposure to AWS or Azure environments for building and integrating cross -cloud data solutions.
• Machine Learning & Advanced Analytics Integration:Experience supporting ML pipelines (Vertex AI) or analytics workflows to enable data science and AI use cases.
Top 3 responsibilities
• Drive Customer Engagement Strategy Execution:
Design and execute customer engagement plans, ensuring consistent communication, improved customer experience, and alignment with business objectives.
• Manage Customer Relationships & Satisfaction:
Act as the primary point of contact for key customers, proactively address concerns, gather feedback, and ensure high levels of customer satisfaction and retention.
📌 Data Engineer with GCP (Sydney)
🏢 Nameless
📍 Sydney
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