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Senior Data Engineer builds scalable data pipelines and a Lakehouse architecture for payments and marketing analytics across AWS and GCP using Dagster/Airflow and IaC.
Design and build Azure Databricks-based Lakehouse pipelines and Spark ETL workflows to power analytics and BI, optimizing cloud data architectures for scale and quality.
Build and maintain a modern data architecture using AWS, SQL, Python, and Power BI to support AI, marketing, development, and cybersecurity projects.
Designs and automates data pipelines, manages APIs, and ensures FAIR data governance to turn scientific data into strategic assets for global R&D decisions.
Design and maintain scalable data pipelines on Databricks using Spark, Delta Lake, and Unity Catalog, collaborating with data scientists and architects to deliver production-grade solutions.
Builds scalable data pipelines using Databricks, Spark, Airflow and Iceberg to power modern lakehouse platforms for Atos’ digital-transformation projects.
Builds ETL pipelines and manages a lakehouse to turn scientific data into FAIR-compliant assets, supporting global R&D decisions at a climate-focused agri-tech company.
Designs and implements AWS-based data pipelines and ETL/ELT workflows, building scalable Lakehouse architectures with Spark and infrastructure-as-code.
Designs and builds scalable data platforms, lakehouse architectures, and ETL/ELT pipelines to support analytics and AI workflows in a hybrid, international team.
Design and build scalable cloud data pipelines using Azure Data Factory and Databricks, then model and optimize datasets for Power BI analytics and reporting.
Design and evolve a modern data platform using Databricks to build scalable Lakehouse pipelines and real-time analytics for ML and decision systems.
Build and maintain data pipelines and ETL workflows in Python, orchestrating data ingestion from multiple sources for an AI-powered fintech using Kubernetes, Airflow, and cloud platforms.
Build and maintain data pipelines, manage distributed databases, and support development teams using SQL, PySpark, and streaming tech like Kafka.
Builds and maintains AWS-based data pipelines using Glue, Spark, Lambda, and S3 to move and transform data for analytics and reporting.
Design and build scalable Azure data pipelines and Lakehouse architectures using ADF, Synapse, PySpark, and Delta Lake, ensuring secure, governed data flows for enterprise clients.
Build and scale a modern data platform using Databricks and Azure Data Factory to power advanced analytics, ML models, and near-real-time decision systems.
Builds and maintains data pipelines on Azure and Microsoft Fabric, ingesting batch/streaming data with PySpark/Databricks and orchestrating workflows via Data Factory and ADX.
Designs and implements enterprise-scale data architecture for a large transport business, ensuring scalable, secure BI and analytics across multiple countries using AWS, Databricks, and Snowflake.
Build and operate a global renewable-energy data platform, engineering pipelines and AI-ready datasets on Azure/Microsoft Fabric to power analytics and ML at scale.
Designs, builds, and maintains Azure-based data pipelines and lakehouse architectures using Databricks, Synapse, and Data Factory to deliver clean, reliable datasets for analytics and AI.
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