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Senior Data Engineer builds scalable pipelines, warehouses (Snowflake), and ML workflows in Azure to power analytics and AI agents, collaborating with scientists and product teams.
Build Databricks pipelines and migrate data from Amazon Redshift to Databricks using AWS S3, Glue, and Athena while implementing data governance practices.
Build and run Linqia’s AWS-based, Kubernetes-powered influencer marketing platform, automating deployments with Terraform, Jenkins, and GitOps while optimizing cloud costs and reliability.
Design and maintain secure, scalable Azure cloud infrastructure using Terraform, CI/CD pipelines (Jenkins/GitHub Actions), and Linux automation for global tech teams.
Build and maintain scalable Java/Spring Boot microservices, REST/GraphQL APIs, and secure multi-tenant systems in a cloud-native environment.
Build and maintain Factored OS, a modular full-stack platform enabling internal teams to ship tools efficiently, using Node.js/React and cloud infrastructure.
Build and scale an on-premise Kubernetes-based data platform for a global payments unicorn, blending SRE, data, and ML engineering to support real-time transactions and GenAI services.
Builds and maintains a secure, self-service data platform for engineers using Databricks, Delta Lake, Terraform, and CI/CD pipelines to enable global data access.
Build and maintain a self-service data platform for a large food retailer, enabling teams across Europe to securely ingest and process data using cloud-native tools like Databricks, Delta Lake, and Azure.
Senior Data Platform Engineer builds and maintains a self-service data platform for Ahold Delhaize teams, enabling secure, scalable data ingestion and processing using Python, Databricks, Delta Lake, and Azure.
Build and optimize a scalable data platform using Python, Databricks, and Azure, automating pipelines and infrastructure with Terraform and CI/CD.
Build and scale secure, efficient data platforms in Azure using Databricks and Kubernetes, design medallion architectures, and implement PySpark/SQL pipelines for government AI initiatives.
Build and scale managed data products on Snowflake using dbt, integrating internal and external sources to create reliable, AI-ready data foundations for data scientists.
Design and operate Microsoft Fabric-based data platforms, building scalable ETL/ELT pipelines in Python and PySpark to support clean-energy infrastructure analytics.
Designs and builds scalable cloud-native data platforms and pipelines for healthcare clients, using Azure/AWS/GCP, Databricks, Airflow, and Kafka to enable secure, compliant analytics and governance.
Designs, builds, and maintains high-quality .NET applications and services in a complex landscape, driving end-to-end delivery, CI/CD, and cloud migration to Azure while applying DDD and architecture best practices.
Build and maintain Nebul’s Nexus platform in Go, automating Kubernetes clusters, storage, and networking to deliver a sovereign AI cloud for European customers.
Design and maintain Azure DevOps CI/CD pipelines, Infrastructure as Code with Bicep, and Azure security controls for cloud-native applications.
Build and lead Atlas’s identity and access management systems, designing authentication (OAuth, SSO) and authorization (RBAC, ABAC) features while mentoring peers on UI/UX best practices.
Design and implement secure, compliant Azure cloud platforms using IaC and DevOps practices, aligning with European and sovereign cloud standards.
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