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Senior Data Engineer builds GCP-based lakehouse pipelines in Python/Spark, enabling cross-platform data sharing between BigQuery, Snowflake, and Databricks using Iceberg UniForm, Delta Sharing, and Kafka CDC.
Design and maintain scalable AWS data pipelines using PySpark and Python, building ETL/ELT workflows with Glue and Step Functions.
Design and implement analytics workflows and data pipelines in SQL, Python, and Databricks for Aon’s lakehouse architecture to power dashboards and reports.
Data Analyst builds and maintains data pipelines, ETLs, and dashboards using Python, PySpark, DBT, and Streamlit in Databricks on Azure for a logistics client.
Build and operate high-reliability data pipelines that ingest cardiac device data into a MedTech platform, using Python/TypeScript on AWS with Temporal and Kubernetes.
Grupo Seresco busca un/a Big Data & AI Engineer para unirse al equipo Data & AI. Por favor, asegúrese de leer atentamente los siguientes detalles antes de enviar cualquier solicitud. La persona reportará al…
Builds and migrates a modern data platform using Databricks, focusing on creating anonymized Data Marts, ensuring data quality, compliance, and optimizing Spark/PySQL pipelines.
Enterprise Architect driving large-scale digital transformation across Telecom, Energy, Public Sector, and BFSI, focusing on cloud architecture, data platforms, and AI/ML including Generative AI.
The Senior Principal Data Architect will design and maintain enterprise data architecture strategies using AWS and the Databricks Lakehouse ecosystem. This role involves leading data governance, mentoring teams, and integrating generative AI tools into daily data modeling and pipeline development workflows.
The AI Engineer will design, develop, and deploy scalable agentic AI systems and generative AI applications using the Databricks platform. This role involves collaborating with data scientists and engineers to integrate AI models into production environments while utilizing Python, SQL, and modern cloud architectures.
Principal Engineer defines the technical vision for Acceldata’s Open Data Platform, leading architecture and open-source contributions for scalable, distributed data systems powering enterprise analytics and AI.
The Senior Data Engineer will lead the design and implementation of enterprise-wide data quality frameworks and scalable data pipelines. The role involves working with Databricks, Delta Lake, Power BI, and Informatica to ensure data reliability and drive business insights.
Lutech SpA, nel contesto della practice Data Analytics, cerca un Data Engineer per progettare e realizzare soluzioni dati moderne nell ecosistema Microsoft Fabric e Azure, collaborando con referenti tecnici e business.…
Come Data Engineer all'interno della practice Data Analytics , avrai modo di lavorare alla progettazione e realizzazione di soluzioni dati moderne nell'ecosistema Microsoft Fabric e Azure , interfacciandosi con…
Builds and owns cloud-based data infrastructure to handle 100TB–1PB-scale energy grid simulations, ensuring fast, reliable data access for modeling and analysis teams.
Data Engineer II building and operating scalable ETL pipelines and data infrastructure for Amazon's FBA Central Analytics, using Spark/PySpark, dbt, Airflow, and SQL on AWS.
Salary: £53,000 - 82,000 per year Requirements: Enterprise data architecture experience. Experience with Databricks. Experience with Snowflake. Experience with AWS and/or GCP. Experience designing modern cloud data…
Salary: £45,000 - 70,000 per year Requirements: Proficiency in Python and SQL, with experience in Apache Spark. Strong experience building backend services and APIs. Solid understanding of relational databases such as…
Salary: £100,000 - 100,000 per year Requirements: Experience as a Lead Data Engineer or Senior Data Engineer Expertise in designing and building data platforms end-to-end Deep hands-on experience with cloud-native data…
Senior Data Engineer designing and building scalable cloud-native data platforms, implementing near-real-time event-driven ingestion pipelines, and optimizing Spark/PySpark workflows with CI/CD best practices.
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