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Senior Data Engineer builds and optimizes cloud-based data pipelines for clients in energy, transport, finance, and healthcare, using Spark, Kafka, and cloud platforms like Azure/GCP.
Lead a team building cloud-based data pipelines and warehouses using Databricks, Snowflake, and Azure Fabric to deliver analytics and AI solutions for enterprise clients.
Build and maintain scalable data pipelines and ML services for real-time analytics and recommendations using Python, Spark, Kafka, and cloud platforms.
Build and optimize Snowflake-based data pipelines and dbt models for enterprise clients, ensuring robust data architecture, governance, and performance under the Modern Data Stack.
Design and deploy end-to-end data analytics solutions on Azure and Microsoft Fabric, building modern data platforms, ETL pipelines, and Power BI reports for enterprise clients in finance, healthcare, mobility, and climate sectors.
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 and reporting.
Lead a team building scalable GCP data pipelines and cloud data warehouses for enterprise clients, using BigQuery, Dataflow, and DevOps practices to enable data-driven decisions.
Senior Data Engineer building scalable Databricks pipelines in Scala/Python, optimizing Spark workloads, and coaching teams on cloud data architectures for enterprise clients.
Senior Data Engineer at Talan builds and optimizes Databricks/Spark pipelines for large-scale data integration, coaching teams and advising clients on cloud and real-time streaming tech.
Build and optimize cloud data pipelines for clients using Spark, Kafka, and cloud platforms like Databricks or Azure, ensuring scalable, real-time data solutions.
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.
Lead Data Engineer designs and optimizes scalable big-data pipelines and architectures for clients, using Spark and Kubernetes.
Design and deploy modern data analytics solutions on Microsoft Azure and Fabric, building ETL pipelines and optimizing data models for BI insights.
Build and optimize data pipelines on AWS for clients, focusing on automation, Spark, and CI/CD to enable scalable analytics and business insights.
Design and maintain scalable data pipelines on Databricks using Spark, Python, Scala, and SQL to collect, store, and process large volumes of data for analytics and AI workloads.
Designs, builds, and maintains scalable data pipelines and streaming architectures using Spark, Kafka, and Python, while enforcing data quality, observability, and CI/CD practices for enterprise clients.
Build and maintain scalable data pipelines on Databricks, integrating diverse sources and industrializing ML models for enterprise clients.
Design and build scalable Snowflake-based ELT pipelines, optimize SQL workloads, and model data warehouses for modern data platforms.
Design and build scalable data pipelines and cloud-based data platforms for clients, using tools like Terraform, Spark, Kafka, and Snowflake.
Senior Data Engineer builds and maintains cloud-based data pipelines for enterprise clients, using Python, SQL, dbt, and Airflow to integrate, transform, and deliver reliable analytics-ready data.
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