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A senior consultant role at Slalom Build: the engineer designs, builds, and optimizes data pipelines and architectures on AWS to deliver data solutions for clients, while mentoring junior teammates and contributing to Slalom's accelerators and methodologies.
Slalom is a people-first global technology and analytics consultancy. The Analytics Engineer role (Senior Consultant or Consultant) centers on building semantic layers, enabling self-service analytics, and delivering…
Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries…
As an AI/ML Architect at Slalom Build, you will design and deliver enterprise-scale, production-grade AI systems using generative AI, agentic workflows, and cloud-native engineering. You will work with clients to build intelligent products and platforms as part of their digital transformation.
Slalom is seeking an AI/ML Architect to design and deliver production-grade AI systems across AWS, Azure, and Google Cloud. You will partner with clients to shape strategy, define secure architectures, and move AI…
Slalom Build is seeking a data engineer to join our Australia practice, delivering modern data platform solutions for clients across AWS, Azure and GCP. You will design, build, and optimize data pipelines, warehousing,…
Designs, builds, and optimizes cloud data platforms on AWS, Azure, and GCP to support AI-assisted decision-making and scalable data products.
Design and deliver modern data platforms for clients using Snowflake and Databricks across AWS, Azure, and GCP.
Design and build scalable cloud data platforms on AWS, Azure, and GCP using Snowflake, Databricks, and streaming tools to deliver real-time analytics and automated decision-making for enterprise clients.
Designs and builds scalable data platforms for AI and analytics, collaborating with architects and data scientists to deliver robust solutions.
Design and deliver AI-ready data platforms, ML pipelines, and GenAI-specific data flows for clients using cloud ecosystems like AWS, Azure, and GCP.
Design and deliver enterprise-scale AI-enabled data platforms, lead engineering teams, and implement cloud-based ML pipelines for clients using AWS, Azure, GCP, Snowflake, and Databricks.
Leads data/AI platform architecture and ML pipelines for clients, designing secure, scalable solutions on AWS/Azure/GCP and deploying GenAI systems.
Design and build scalable data platforms on AWS, Azure, and GCP, using cloud warehouses, Spark, Kafka, and Python/Java to enable AI-driven analytics for enterprise clients.
Designs and builds scalable cloud data platforms across AWS, Azure, and GCP, leading AI-driven data pipelines and architectures for enterprise clients.
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