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Build and maintain high-performance data pipelines for a real-time ad-tech platform, enabling ML models with clean, scalable data while working in a fast-paced engineering team.
Build and own scalable data platforms and ETL pipelines for AI/ML and quantum-inspired optimization products, ensuring clean, versioned, and accessible datasets for analytics and AI workflows.
Build and maintain data pipelines using Spark, PySpark, and AWS services to process batch and real-time data for clients.
Lead Data Engineer defines data processes, ensures end-to-end traceability, and bridges business needs with technical teams in a banking client, using Airflow, PySpark, Kafka, and AWS.
Design and maintain Snowflake-based data pipelines and warehouses that feed credit risk models, analytics, and reporting for a global distributor’s credit function.
Build and maintain scalable cloud data pipelines for a global travel platform, using AWS, Kafka, Spark, and Scala to process billions of daily events.
Build and maintain scalable data pipelines and production-grade ML systems for clinical trials, pharmacovigilance, and drug manufacturing at a global pharma company.
Designs and builds scalable data pipelines and cloud architectures on Google Cloud Platform, ensuring high-quality data for analytics and AI workloads.
Build and maintain scalable data pipelines and platforms using Spark, Scala, Kafka, and cloud tech to enable analytics and decision-making across BNP Paribas.
Senior Data Engineer builds scalable data pipelines, ETL/ELT processes, and cloud-based analytics platforms using Python, Spark, AWS, and modern data stacks to power AI-driven solutions.
Senior Data Engineer builds and scales reliable, high-quality data pipelines and governance at a global market-research analytics firm using Python, SQL, Airflow, Spark, and AWS.
Senior Data Engineer builds and maintains scalable data pipelines and models for a leading aeronautics client, ensuring data quality and security while collaborating with analytics and AI teams using Python, SQL, Snowflake, and Airflow/DBT.
Senior Data Engineer to own and scale a GCP-based data warehouse, build robust pipelines, and unify diverse data sources for a leading online education group.
Build and maintain scalable data pipelines and cloud architectures to ingest, transform, and serve reliable data for analytics and reporting across hybrid environments.
Build and maintain ETL pipelines, optimize MongoDB schemas, and create Metabase dashboards to power AI-driven travel rental analytics and reporting.
Build and maintain a modern data platform in AWS/Snowflake, designing pipelines with Python/SQL and orchestrating with Airflow/Dagster to power analytics and reporting for a crypto-fintech platform.
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 and models for a mobile-gaming company, enabling analytics and AI-driven workflows with Python, SQL, and cloud warehouses like Snowflake.
Senior Data Engineer to design and build a greenfield data infrastructure for AI-driven growth, including pipelines, warehousing, and analytics for product, CRM, finance, and marketing teams.
Build and run the AIOps platform that keeps AI models, LLM pipelines, and agents reliable, scalable, and cost-efficient in AWS/Azure.
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