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Mid-level Data Engineer builds and maintains data pipelines to support revenue decisions, collaborating with marketing, sales, and finance using SQL, Python, Databricks, and Google Cloud Platform.
Builds and maintains scalable data pipelines using Scala, Apache Spark, and cloud platforms to process and analyze large datasets.
Builds and optimizes data pipelines and infrastructure in Python and SQL, deploying with Docker and Kubernetes to support high-stakes risk analysis.
Builds and maintains Palantir Foundry data pipelines to enable AI/ML workflows using Python, SQL, and ML libraries.
Builds and maintains an open geospatial database of ancient European coins, aligning data with international ontologies and adding images via ARK and Nakala.
Designs and builds dbt models and optimizes Snowflake data pipelines for analytics in a hybrid work setup.
Build and optimize Azure Synapse data pipelines and ETL/ELT processes, model data, and collaborate with business teams to deliver AI and analytics solutions.
Designs and optimizes cloud data pipelines using Snowflake, dbt, and advanced SQL for international projects, implementing ELT architectures and automated testing.
Build and optimize cloud-based ETL pipelines and Snowflake data models for a modern product team.
Builds and maintains cloud-based data pipelines and analytics infrastructure for a global SaaS platform, ensuring high-quality data flows for BI teams.
Builds and maintains Azure Databricks-based data pipelines and lakehouse architectures, integrating SQL Server sources to support scalable analytics.
Designs and builds Azure Databricks Lakehouse data pipelines and ETL/ELT workflows using SQL Server, ensuring data quality and performance.
Senior Manager Data Engineer builds and maintains scalable data pipelines and warehouses for a global healthcare company, integrating SAP, Salesforce, and cloud platforms.
Design and build a global lakehouse platform for payments and marketing analytics using AWS/GCP, Dagster/Airflow, and medallion-layer pipelines.
Senior Data Engineer at KPMG España builds and optimizes large-scale data pipelines using PySpark and Python to support critical business decisions.
Build and maintain ETL pipelines and data warehouses in Snowflake and AWS, modeling raw and business data vaults for a large-scale migration effort.
Designs and builds scalable Azure and Fabric data pipelines, from ingestion to BI insights, in an aeronautics environment with a hybrid work model.
Builds and maintains large-scale data pipelines for financial clients using Spark, Scala, and Python, ensuring scalable and robust data solutions.
Build and deploy scalable data-labeling solutions for AI models, working with customers and translating needs into technical configurations using Python.
Build and optimize data infrastructure for a mobile ad-tech platform, ensuring real-time analytics and seamless data flow across platforms using Python and modern storage/orchestration tools.
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