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Build and maintain data pipelines using Snowflake and Git, troubleshoot integrations, and support analytics platforms for a top AFL club.
Build and maintain data pipelines and customer datasets for REA’s property platform, consolidating legacy systems into a unified customer profile to enable AI-driven personalization.
Builds and maintains cloud data pipelines using Azure Databricks, PySpark, and Delta Lake to power analytics and BI in a modern Lakehouse architecture.
Build and scale ETL/ELT pipelines in PySpark and SQL, model enterprise data, and ensure quality and lineage for downstream analytics at a large IT consultancy.
Build and maintain cloud-based data pipelines and warehouses using SQL, Python, Snowflake, and AWS to power analytics and reporting for clients.
Data Engineer to migrate and govern data assets from BigQuery Sandbox to a managed Google Cloud Platform environment, building reliable ETL/ELT pipelines.
Build and maintain ETL/ELT pipelines using Databricks, Snowflake, or Informatica to integrate data into cloud warehouses, optimizing performance and troubleshooting issues in a managed-services environment.
Builds and maintains data platforms and AI-driven insights for enterprise clients, working with large datasets and collaborating across teams.
Designs and builds scalable data pipelines and workflows in a collaborative team, writing clean, maintainable code to deliver high-quality data solutions.
Builds and maintains real-time data pipelines and databases using SQL and Python to power analytics that guide business strategy.
Design and maintain scalable ETL pipelines using Databricks, Python, and SQL to ensure reliable data solutions in a cloud environment.
Build and maintain data pipelines, optimize warehouse performance, and automate data flows to turn raw data into actionable insights for business needs.
Designs and builds data pipelines to move and transform data efficiently, writing maintainable code while collaborating with cross-functional teams in an agile environment.
Builds and maintains databases and data pipelines using SQL and Python to power real-time analytics and business decisions.
Build and optimize data pipelines, write clean code, and collaborate with teams to deliver reliable data solutions using batch, streaming, or hybrid approaches.
Designs and maintains scalable data pipelines on Databricks, building ETL/ELT processes for large datasets using Python and SQL.
Designs, builds, and optimizes data pipelines for a fintech company, ensuring reliable data flow to the warehouse using cloud tools like AWS/Google Cloud, Spark, and Kafka.
Builds and optimizes enterprise data pipelines and Lakehouse layers using Microsoft Fabric, Power BI, and Dataverse to support AI-driven analytics and reporting.
Builds and maintains large-scale data pipelines on Azure Databricks and Spark, writing PySpark/Python and SQL to process TB-scale datasets and ensure data quality.
Builds and maintains scalable data pipelines to feed AI models, ensuring clean, reliable data for decision-making in a hybrid office setup.
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