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Senior Data Engineer builds and optimizes cloud-based data pipelines and warehouses using Spark, Kafka, and cloud platforms (Databricks, Snowflake, Azure) to enable real-time analytics and reporting for enterprise clients.
Build and optimize custom data architectures, pipelines, and visualizations for clients, primarily using Python, PySpark, and cloud/GCP, with Java as a bonus.
Builds and maintains ETL/ELT pipelines, models data in a warehouse, and creates Power BI dashboards to support business teams.
Data Engineer builds and maintains data pipelines and BI dashboards for a national public-transport operator using Microsoft Power Platform.
Build and maintain high-volume data pipelines on GCP using BigQuery, dbt, and Airflow, optimizing performance and ensuring data quality for analytics.
Designs and builds scalable data pipelines, integrates cloud data warehouses, and embeds AI models for clients in retail, energy, and industry using Snowflake, dbt, Talend, Python, and cloud platforms.
Lead a data team to build ETL/ELT pipelines and reporting that drive operational excellence for airport assistance services.
Design and deploy robust ETL/ELT pipelines, orchestrate workflows with Airflow, and build modern data stacks on Denodo, Dremio, Trino, and Iceberg in Kubernetes environments for public-sector clients.
Build and optimize cloud-based data pipelines for clients in finance, healthcare, logistics, mobility, and climate sectors using Spark, Kafka, and cloud platforms like Azure/GCP.
Build and optimize end-to-end data pipelines on Databricks and Spark, integrating real-time and batch data for analytics and AI use cases.
Leads the migration of an on-premise data warehouse to the cloud, auditing existing systems, designing scalable cloud architectures, and guiding teams through implementation and documentation.
Build and maintain end-to-end data pipelines and modern data stacks for clients, using cloud DWHs (BigQuery/Snowflake), orchestration (Airflow, dbt), and SQL/Python to deliver reliable, analytics-ready data and BI solutions.
Lead Data Engineer building scalable, reliable data pipelines in Snowflake using SQL, Python, and DataOps practices to ensure high-quality, observable data flows for analytics.
Design and build end-to-end data pipelines on Microsoft Azure, using Data Factory, Data Lake, SQL DB and Analysis Services to deliver production-ready analytics and AI platforms.
Leads a team to design and deploy robust data pipelines and distributed architectures using SQL, Kafka, and ELK, while mentoring junior consultants.
Build and maintain scalable ETL/ELT pipelines on Databricks (Spark SQL, PySpark, Scala) to feed reliable, high-performance data for analytics and decision-making.
Build and maintain cloud-based data platforms (datalakes, ETL pipelines) for enterprise clients, using AWS/GCP/Azure, Python, Airflow, and DevOps tools.
Build and deploy Microsoft-based data pipelines and cloud solutions for clients, focusing on Azure data services and AI/ML integrations.
Builds ETL pipelines, integrates data sources, and creates Power BI dashboards in a cloud-based BI environment using Python and GCP/AWS.
Designs and builds AI-ready data pipelines and architectures for client projects using Python, SQL, dbt, Airflow, and BigQuery/Snowflake/Databricks in a CI/CD environment.
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