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Build proof-of-concept software for UK government projects using modern full-stack tools and cloud platforms.
Designs and implements cloud-based data architectures (AWS, Azure, GCP) and real-time pipelines (Kafka, Snowflake, Databricks) to align client business goals with modern data solutions.
Job Requirements: 5-6 years of overall IT experience, with 2+ years of hands-on experience working with Neo4j,Cypher query language, and Graph Data Science (GDS) library. Strong proficiency in Python for ETL pipelines,…
Designs and implements cloud-based data architectures (AWS/Azure/GCP) and pipelines to improve data integration, quality, and delivery for enterprise clients.
Build and scale core data infrastructure (storage, streaming, caching, indexing) to support large AI models, using MongoDB, Postgres, Kinesis, Flink, Spark, ElasticSearch, and Redis.
Build real-time data pipelines and ML workflows on AWS to power AI-driven customer experience features, integrating LLMs and agentic systems for workforce management.
Designs and builds real-time data pipelines on AWS using PySpark, Airflow, and Redshift to power enterprise-scale analytics and insights for an HR-focused SaaS platform.
Data Engineer | Sydney, NSW We are looking for an experienced Data Engineer (9–14 Years) to join a high-performing team delivering enterprise-scale data platforms and real-time data solutions on AWS. Must Have Skills…
Design and build scalable data pipelines using PySpark, Databricks, and Azure services to transform raw data into business insights for Toyota Finance Australia’s automotive financing operations.
Build and maintain cloud-based data pipelines for batch and streaming analytics, using Python, SQL, Kafka, Airflow, and GCP/AWS services to power business insights and ML at a fast-growing Q-commerce platform.
Build and maintain ETL pipelines and data models using Python, SQL, PySpark, and AWS services for store operations and sales analytics.
Lead engineer building a real-time financial data hub using Java/Spring Boot and Kafka, migrating from batch to event-driven pipelines while mentoring the team.
Design and build scalable data pipelines and architectures using AWS and Databricks, focusing on PySpark, Python, and SQL to enable advanced analytics and ETL workflows for enterprise clients.
Senior engineer building scalable data infrastructure for real-time network security analytics using Python, Kafka, and Kubernetes in a cloud-native environment.
Build and maintain scalable data pipelines and cloud-based analytics platforms using Snowflake, Databricks, and Python, ensuring reliability, performance, and governance.
Lead a team to design and build scalable AWS-based data pipelines, warehouses, and real-time analytics using Python, Snowflake, and orchestration tools.
Build and scale a cloud-native data platform in AWS (S3, Iceberg, Spark, Airflow) to process 100M+ objects with sub-500ms latency APIs for a new UK consumer credit bureau.
Build and maintain scalable data pipelines and infrastructure for a talent-cloud platform, enabling analytics and AI-driven features using Python, SQL, cloud services, and streaming tech.
Designs and implements cloud/hybrid data pipelines, advanced analytics, and AI-driven solutions (e.g., ML models, dashboards) to transform raw data into actionable insights for enterprise clients. Core tech: Azure/AWS/GCP, Python/SQL, Spark, Kafka, and Azure OpenAI.
Lead the design and scaling of a modern data platform, building robust pipelines and mentoring engineers to ensure reliable, governed data foundations for analytics and reporting.
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