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Data Engineer building ETL/ELT pipelines in a Lakehouse environment using Databricks (Unity Catalog), Spark, and Azure Data Factory, collaborating with architects and analysts on a greenfield data platform.
Senior Data Platform Engineer designing and overseeing data pipelines in Databricks on AWS, transforming raw data into analytics-ready datasets while contributing to governance and scalable lakehouse design in a hybrid Sydney office.
Data Architect/Senior Data Engineer designing and building data infrastructure for governance at scale on Databricks, including data retention automation, DSAR pipelines, access control, and metadata integration. Core technologies include Databricks (Unity Catalog, Delta Lake, Spark), AWS, Terraform, and data governance tools.
Data Engineer role developing and optimizing data pipelines using Azure, Databricks, PySpark, and Azure Data Factory within a Data Warehouse Cloud environment, with responsibilities spanning both data engineering and DevOps/infrastructure tasks.
LabSoft is seeking an experienced Data Engineer to design, industrialize, and optimize cloud-based data pipelines on Azure using Databricks and PySpark. The role involves managing data workflows, implementing CI/CD practices, and collaborating with business teams to improve performance and cost efficiency.
Data Engineer designing and implementing lakehouse solutions and automated pipelines using Azure and Databricks, migrating legacy pipelines to Delta Lake-based offerings while collaborating with IT and business partners in an Agile environment.
Senior DataOps/Cloud Data Engineer for a large public-sector data modernization initiative, designing and building cloud-based data pipelines and lakehouse solutions using Azure Data Factory, Databricks, Informatica, Python, and SQL.
Design and operate Microsoft Fabric workspaces, Lakehouse architecture, and CI/CD pipelines to deliver trusted dimensional models and Power BI semantic models for auto and property insurance data. Core technologies: Microsoft Fabric, Azure DevOps, SQL, PySpark, Delta Lake, and Power BI.
Python Developer (contract, 1 year) building scalable microservices, APIs, and data engineering solutions using FastAPI, Docker, Kubernetes, Azure Databricks, and Kafka for a large banking client's platform modernization in Toronto.
Full Stack Engineer building SOTA video generation foundation models, developing microservices, AI training data platforms, big data infrastructure, and React/TypeScript frontends.
The Data Engineer designs and maintains data pipelines and integrations to support GEI's AI solutions and digital initiatives. The role involves building ingestion pipelines, managing data stores for RAG, and ensuring data quality and governance using Azure technologies.
Lead the design and delivery of end-to-end Microsoft Fabric data solutions (Lakehouse, Warehouse, Pipelines, semantic models) for multiple consulting clients, combining hands-on T-SQL/PySpark/Python engineering with architecture, CI/CD via Azure DevOps/GitHub Actions, and mentoring.
The Senior Data Engineer will work on digital transformation projects using Azure, focusing on building scalable data pipelines. Key technologies include Apache Spark, Databricks, MongoDB, and Delta Lake within a DevOps and Agile environment.
Principal Data Engineer architecting and deploying scalable big data systems, ETL/ELT pipelines, and AI infrastructure foundations using distributed computing frameworks (Spark, Flink), streaming platforms (Kafka), cloud data warehouses, and data lake architectures.
The Data Engineer will design, build, and maintain reliable data ingestion and transformation pipelines using AWS and Databricks. The role involves developing data processing layers, ensuring data quality, and collaborating with cross-functional teams to deliver production-ready data solutions.
Design and implement scalable ETL pipelines and data connectors on Azure Databricks, ensuring data quality and smooth deployment using SQL, relational database design, and Delta Lake.
Mid-level Data Engineer building and maintaining scalable data pipelines and ETL/ELT processes using Databricks, Apache Spark, and cloud platforms (Azure/AWS/GCP) at an engineering services firm.
A Data Engineer building and modernizing cloud data pipelines, migrating legacy ETL workflows, and implementing Delta Lake medallion architecture using AWS, Databricks, Informatica, PySpark, and SQL.
The Senior Data Engineer will design and maintain scalable ETL/ELT pipelines within a Databricks Lakehouse environment to support BI and AI initiatives. This hybrid role requires expertise in Python, SQL, and Azure cloud services, emphasizing software engineering best practices like CI/CD and Infrastructure as Code.
The Data Engineer will modernize and scale cloud data platforms by building ETL/ELT pipelines using Databricks, Informatica (IDMC), and AWS. The role involves migrating legacy workflows to PySpark and SQL while managing data governance and infrastructure performance.
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