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Build and maintain scalable data pipelines using DBT and SQL to transform raw data into reliable, analytics-ready models for modern data warehouses.
Design and operate a secure, GDPR-compliant data lake for identity verification and AI research, building storage, APIs, and orchestration tools that handle sensitive biometric and KYC data at scale.
Builds and maintains data pipelines and platforms to ensure reliable, accessible data for a life-insurance and finance company.
Designs, builds, and maintains critical data pipelines using Semarchy xDI, optimizing batch processing and performance for a data-focused product company.
Lead a team of data engineers to build scalable data pipelines and cloud infrastructure (AWS/GCP/Azure) using Spark, Kafka, and Terraform, while collaborating with data scientists to industrialize models.
Designs and maintains scalable data pipelines in Python, SQL, dbt, and Airflow, ensuring data quality and governance across BigQuery, Snowflake, and Databricks to support AI-driven workflows.
Design and build robust cloud data architectures on Microsoft Fabric and Azure for enterprise clients, from ingestion to production, using Data Vault 2.0, Azure Data Factory, Synapse, and Data Lake.
Builds and maintains data pipelines from raw sources to curated layers using dbt, BigQuery, and Looker for analytics and data science teams in a retail media context.
Designs and optimizes data ingestion and transformation pipelines in Python and SQL, deploys modern data platforms on Azure/AWS/GCP, and ensures observability and cost efficiency.
Build and maintain a unified data platform on Azure and Fabric, ingesting, storing, and serving data for analytics and reporting while collaborating with analysts and business teams.
Designs and maintains MuleSoft Anypoint and Talend data-integration APIs and pipelines, ensuring secure, well-documented architectures that meet business needs.
Designs and builds end-to-end AI solutions, from use-case discovery to production deployment, using ML/DL and industrialization best practices.
Build and maintain scalable data pipelines on Databricks, integrating batch and streaming sources while ensuring governance, security, and performance for analytics and AI projects.
Build and maintain scalable data pipelines on Databricks and cloud, ensuring data quality and governance while collaborating with data scientists and architects.
Senior Data Engineer builds and optimizes cloud-based data pipelines on AWS, mentors junior engineers, and collaborates across teams to scale data infrastructure.
Senior Data Engineer designs and implements Microsoft Fabric and Azure-based data solutions, integrating ETL pipelines, BI, and AI for enterprise clients while collaborating with cross-functional teams.
Lead Data Engineer designing Snowflake-based data architectures and dbt pipelines for enterprise clients, modernizing data infrastructure and optimizing data flows.
Designs and builds cloud-based data pipelines and analytics platforms on Microsoft Azure or GCP, using ETL tools, SQL, Python/Java/Scala, and data-lake architectures to deliver business insights.
Build and maintain a unified data platform on Azure and Microsoft Fabric, designing robust data pipelines and BI solutions using Azure Data Factory and SQL.
Build and maintain scalable ETL/ELT pipelines on Databricks using Spark SQL, PySpark, and Scala to feed reliable, high-performance data for analytics and decision-making.
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