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Principal Data Engineer builds and leads a scalable data platform at an e-commerce photo-products company, focusing on trustable, decentralized data adoption and AI-driven customer experiences.
Principal Data Engineer designs and maintains secure, scalable data platforms and pipelines for Defence/Aerospace programmes, using cloud-native tech and DataOps to enable analytics and digital transformation in regulated environments.
Build and maintain scalable data pipelines and ML infrastructure for real-time energy market analytics using Python, AWS, and Airflow.
Build and maintain scalable data pipelines and curated datasets in Snowflake using dbt, Airflow, and Terraform to power CRM analytics and insights for Zendesk’s support operations.
Build and maintain scalable data pipelines and cloud infrastructure on Google Cloud, ensuring data quality and enabling analytics for clients.
Principal Data Engineer builds and leads data pipelines and foundations using Databricks, PySpark, Python and SQL to enable an energy trading company to extract value from data.
Build and maintain cloud-native MLOps and data pipelines for a biotech firm, deploying and scaling ML models in AWS/GCP while ensuring reliability, security, and reproducibility.
Build and maintain scalable data pipelines and storage systems to power fraud detection, analytics, and reporting using Python, SQL, and orchestration tools like Airflow.
Design and build a scalable data infrastructure for a global PE fund using Snowflake, dbt, and Azure Data Factory to support analytics and AI initiatives across investment teams.
Build and maintain scalable data pipelines and ETL processes in Python and SQL, using Snowflake, Airflow, and Kafka to deliver high-quality commodity-market data for analytics and AI-driven insights.
Designs and maintains scalable AWS-based data pipelines using SQL, Spark, Kafka, and Python to process large datasets and deliver analytics for business insights.
Senior Data Engineer builds scalable ETL/ELT pipelines and cloud-native data infrastructure for a high-performance digital-asset trading firm, ensuring reliable, secure data access in a fast-paced environment.
Builds the data backbone for an AI-driven public-safety platform, integrating legacy systems, cloud services, and real customer data with ETL pipelines and infrastructure-as-code.
Design and maintain scalable data pipelines and architecture for a fast-growing ecommerce company, using Python, SQL, and cloud services like AWS/Azure.
Staff Data Engineer builds and scales cloud-native data pipelines using PySpark, AWS Glue, Spark, and Airflow to modernize global data infrastructure in a regulated environment.
Design and maintain scalable data pipelines for a digital content platform using Apache Airflow, dbt, Python, and cloud tools, ensuring data quality for AI workloads.
Build and maintain scalable data pipelines using Databricks, Snowflake, Airflow, dbt, and Python on AWS to power Moody’s AI-ready digital content platform.
Lead a team of data engineers to design and deploy cloud-native data pipelines and warehouses, migrating IAG Cargo from on-premise to AWS and Snowflake.
Lead a hybrid team of data engineers, define the data strategy, and build scalable pipelines and platforms to support analytics and business-critical initiatives in a financial-services organisation.
Senior Data Engineer builds and maintains cloud-based data pipelines using GCP/AWS, BigQuery, and Airflow to deliver analytics and insights for editorial, marketing, and product teams.
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