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The Senior Data Engineer will build and maintain data ingestion pipelines, lakehouse structures, and CI/CD workflows using AWS and AI-focused technologies. The role involves establishing data engineering standards and implementing data quality and security controls within a hybrid work environment.
Build and optimize scalable backend systems for Vanguard’s fintech platform, integrating data pipelines and APIs while using Python, AWS, and AI-assisted tools.
Build and maintain Databricks pipelines that ingest and transform high-volume external data into clean, structured inputs for analytics and AI models, primarily supporting stakeholder engagement in the energy and utility sectors.
GCP Data Engineer (hybrid in Kitchener) designing and building scalable data pipelines, ETL/ELT workflows, and data ingestion frameworks using BigQuery, Dataflow, Cloud Composer, Dataproc, Python, and SQL.
The Senior Data Engineer will design and build the company's data platform, including pipelines, data models, and orchestration systems. The role focuses on scaling data infrastructure using Python, SQL, and cloud-based data warehousing technologies.
Lead Snowflake-based data lakehouse and pipeline development for RBC Insurance, designing scalable architectures, optimizing performance, and collaborating with stakeholders to drive data-driven business growth.
Senior Data Engineer designing and maintaining enterprise data pipelines and lakehouse architecture using Microsoft Fabric, Azure, SQL Server, and Oracle Cloud Infrastructure for a large dairy cooperative.
The Security Analytics Engineer designs and manages data pipelines and Snowflake models to support security analytics and AI-ready reporting. The role focuses on data reliability, governance, and CI/CD processes within a global gaming environment.
Build and maintain Homeprotect’s GCP-based data analytics platform, designing secure, scalable pipelines with BigQuery, Dataflow, and Cloud Run.
The GCP Data Platform Engineer will design, build, and maintain secure, production-ready infrastructure patterns for Homeprotect's data analytics platform using GCP and Terraform. The role involves supporting data pipelines, managing access controls, and ensuring platform reliability and observability.
Senior Data Pipeline Architect at iGroove building and owning the data ingestion backbone, scaling a decade-long data stack that feeds AI-powered product decisions via production pipelines, crawlers, and integrations.
Builds and maintains AXA’s Lakehouse platform in Google Cloud, developing Python services for data ingestion, quality, and governance while advising teams on platform use.
Senior Data Platform Engineer evolving a Google Cloud Lakehouse platform built on Data Mesh principles, developing Python services for data ingestion, quality, and metadata management to support AXA Switzerland's AI initiatives.
The Data Engineer Solution Specialist designs and maintains data pipelines, models, and analytical workflows to transform complex data into actionable business insights. This hybrid role involves collaborating with cross-functional teams to ensure data quality and integrity across regional and global systems.
Senior Data Engineer building highly scalable, fault-tolerant data ingestion systems processing 5B clickstream events daily using Scala, Spark, Kafka, Beam, BigQuery, PubSub, and Dataflow on a hybrid on-premise/GCP stack.
Senior Analytics Engineer designing and maintaining ELT pipelines and dimensional data models in Google BigQuery using SQL, Python, and dbt to deliver clean datasets to end users.
Senior Data Engineer designing and building high-volume batch and streaming data pipelines on AWS and GCP using Python, Java/Scala, Spark, Airflow, and various SQL/NoSQL databases for a travel marketplace client.
Lead Data Engineer assesses enterprise data sources, designs pipelines, and validates AI use cases for Fortune 500 clients using cloud platforms like Azure and AWS.
Senior Data Engineer designing and implementing scalable data ingestion pipelines across AWS and GCP, mentoring engineers, and owning end-to-end data platforms.
Build and maintain a data platform using Snowflake and AWS, focusing on data ingestion, cloud infrastructure, and modeling while collaborating with data teams.
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