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Build and maintain scalable cloud data solutions for a Swiss health-insurance provider, migrating on-prem data warehouses to Microsoft Fabric and ensuring compliance with healthcare regulations.
Senior Data Engineer builds and maintains a Databricks-on-Azure lakehouse for an insurance/reinsurance client, centralizing SAP and other sources into medallion layers for analytics, reporting, and future AI use cases.
Build and scale Databricks-based data pipelines that ingest, clean, and validate clinical and operational data for ML and healthcare analytics in a med-tech startup.
Build and optimize scalable data platforms and ELT pipelines using Databricks, PySpark, and Delta Lake, while consulting with Swiss clients to translate their needs into robust data solutions.
Build and maintain ETL/ELT pipelines, data architectures, and ML pipelines using Azure Databricks, Python, SQL, and Kafka to drive energy-sector insights and automation.
Senior Data & AI Engineer builds and maintains ML pipelines and MLOps practices for a Swiss energy company using Python, SQL, Azure Databricks, and PowerBI.
Build and maintain a modern data platform using Microsoft Fabric to integrate, transform, and govern healthcare data for a nationwide pharmacy chain.
Build and maintain a modern data platform using Microsoft Fabric to integrate, process, and govern healthcare data for reliable analytics and reporting across Switzerland.
Build and own streaming/batch data pipelines, lakehouse and time-series layers, and self-serve tooling for a crypto market maker’s trading, portfolio, and analytics needs using Python, SQL, Kafka, ClickHouse, and Terraform.
Design and lead cloud-based data platforms and analytics solutions for enterprise clients, translating business needs into scalable architectures using Snowflake, Databricks, or similar tools.
Lead a team building and scaling a next-gen financial-data platform using Python, Spark, and AWS, while setting engineering standards and guiding technical decisions.
Build and maintain data models, quality checks, and metrics in a lakehouse using dbt, Python/pandas, and Airflow to deliver clean datasets for analytics and reporting.
Build and maintain scalable data infrastructure (AWS, Kafka, Spark, Airflow) to power analytics and AI-driven hiring products at a global job-tech platform.
Build and maintain scalable data platforms on AWS using Kafka, Spark, Airflow and Iceberg to power analytics and AI products.
Build and maintain the data infrastructure (Data Lakehouse) that powers AI-driven dental products, collaborating with ML researchers and MLOps engineers.
Build and maintain cloud-based data pipelines in Azure using Databricks, PySpark, and Python, collaborating on end-to-end data solutions for enterprise clients.
Design and build a cloud-based data lakehouse that ingests engineering and security tool data, transforms it through medallion layers, and serves analytics dashboards and AI agents.
Build and lead cloud-native data pipelines for regulatory reporting in investment banking, migrating legacy systems to AWS and integrating AI-driven workflows using Python, Kafka, and Kubernetes.
Design and build scalable cloud-native AI data platforms and pipelines using Python, Spark, and Kafka to power machine learning and GenAI initiatives for enterprise clients.
At Sigma Embedded Engineering , we are currently looking for a Data Platform Engineer to join a team building a new data platform from scratch. The platform will integrate data from several departments and systems,…
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