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Designs and maintains data pipelines using Microsoft Fabric and Azure tools to build scalable analytics platforms for enterprise clients.
Build and maintain scalable data pipelines and cloud infrastructure to move raw client data into clean, secure warehouses for BI and future AI/ML use.
Build and maintain ETL pipelines, optimize MongoDB schemas, and create Metabase dashboards to power AI-driven travel rental analytics and reporting.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and optimize data workflows for enterprise clients.
Designs and maintains scalable data pipelines, ETL/ELT processes, and cloud-based data platforms to support analytics and AI in high-security sectors like defense.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and transform data for clients.
Build end-to-end data pipelines and analytics solutions for Oysho’s eCommerce platform using Databricks, PySpark, SQL, and Power BI to drive business decisions.
Build and maintain data pipelines, warehouses, and lakes for Emburse’s SaaS products using Snowflake, Databricks/Spark, AWS, and Looker.
Build and scale data pipelines, warehouses, and analytics to power a fast-growing second-hand marketplace, analyzing pricing, supply, and conversion to drive business decisions.
Senior Data Engineer builds and scales a unified data ecosystem for 60+ brands, designing ETL pipelines, data models, and governance to power analytics and AI across team.blue’s ecommerce platform.
Builds and scales industrial data pipelines in Azure/Databricks, integrating sensor data with ML models to improve energy efficiency and logistics in a European industrial company.
Build and maintain data pipelines, dashboards, and warehouse models to turn business questions into trusted insights using SQL, Python, and cloud warehouses like BigQuery.
Design and build cloud-native data pipelines on GCP to power analytics and AI, ensuring scalable, governed, and secure data platforms for enterprise use.
Build and maintain scalable data pipelines and AI-driven features for a hospitality analytics platform, using Python, BigQuery, and GCP to power insights and machine learning.
Build and maintain cloud data pipelines and ML solutions on GCP, AWS, and Azure using Python, SQL, dbt, and API-first architectures.
Build and optimize data pipelines (ETL/ELT) in Azure to integrate and clean hotel and guest data, enabling analytics and Power BI dashboards for business decisions.
Build and optimize scalable ETL/ELT pipelines, populate data warehouses and lakes, and secure tenant data for AI-powered analytics across Emburse’s products.
Build and optimize scalable, multi-cloud data pipelines using SQL, Python, and ETL/ELT tools while collaborating with clients and internal teams.
Build and maintain cloud data pipelines on GCP and Databricks, using BigQuery, Airflow, dbt, and Dataflow to feed dashboards and experiments.
Build and maintain AWS-based data pipelines that ingest and transform structured data into Redshift using PySpark, SQL, and ETL/ELT tools.
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