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Build and maintain data pipelines and cloud infrastructure for marketing analytics, using Snowflake, Python, SQL, and cloud platforms (GCP/Azure/AWS) to enable secure data sharing and customer insights.
Build and optimize Snowflake-based data pipelines and cloud databases for clients, focusing on SQL/ETL, modeling (Star Schema, Data Vault), and real-time data flows.
Senior Data Engineer builds and optimizes cloud-based data pipelines for clients in energy, transport, finance, and healthcare, using Spark, Kafka, and cloud platforms like Azure/GCP.
Designs and builds real-time data pipelines for large corporate and investment banks using Python and distributed data frameworks.
Build and maintain robust data pipelines on AWS to process terabytes of media audience, adserver, and CRM data, enabling predictive products and ad-revenue insights.
Build and maintain data pipelines and databases to collect, transform, and deliver data for analytics and reporting using SQL, Python, and Big Data tools.
Build and maintain AI-first data pipelines and dashboards using SQL and Python in Databricks to turn raw data into actionable insights for a product-focused team.
Build and optimize Snowflake-based data infrastructure using Python, SQL, and cloud platforms like GCP, AWS or Azure.
Build and own GraphQL APIs and data pipelines for Morpho’s DeFi products, ensuring sub-second responses at scale while collaborating with frontend and product teams.
Build and maintain data pipelines and cross-platform ML models using TensorFlow and PyTorch to process public and customer data for AI training and backend integration.
Build and maintain robust ETL pipelines, cloud data platforms, and databases to ensure high-quality data for analytics and AI teams using Python, Spark, and cloud services like AWS/Azure/GCP.
Build and maintain large-scale data pipelines and models in Azure or AWS, integrating with Power BI and automating processes using Python or R.
Build and optimize Snowflake-based data products using dbt; design schemas and pipelines in a cloud-native environment.
Builds and maintains data pipelines on Databricks using Spark, Hadoop, Python, and SQL, with exposure to cloud platforms like AWS, Azure, or GCP.
Build and scale high-volume data pipelines for an industrial IoT platform on AWS, using Spark/Flink, Kinesis, Databricks, and FastAPI to deliver real-time and batch analytics.
Build end-to-end data pipelines and self-service dashboards that turn raw data into actionable business insights using SQL, Power BI, and optionally Python or Talend.
Design and build scalable, AI-ready data pipelines using Spark, Kafka, and cloud platforms (AWS/GCP) to power GenAI models and analytics for enterprise clients.
Senior Data Engineer builds scalable data pipelines and AI solutions for Nexans’ digital transformation, leveraging Python, Databricks, and cloud platforms to enable measurable business impact.
Senior Data Engineer builds and optimizes Databricks and Azure pipelines for a major retail company, using Python and SQL to process large-scale data and support AI-driven projects.
Design and build modern data pipelines and architectures using Azure Fabric for a digital transformation consultancy.
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