Senior Data Engineer – Azure Databricks & PySpark (80–100%)For our client, a leading financial institution in Zurich, we are looking for an experienced Senior Data Engineer to join a team responsible for developing and enhancing a modern Data Platform for Analytics and AI.Senior Data Engineer – Azure Databricks & PySpark (80–100%) description: Design, develop, and maintain scalable data pipelines, data products, and backend services supporting analytics, reporting, real-time processing, and AI use cases.Build and optimize large-scale data processing solutions using Databricks, Apache Spark, PySpark, Spark SQL, and Delta Lake.Develop and maintain efficient ETL/ELT pipelines and data transformation processes.Design and implement data models for analytical and operational workloads.Write high-quality, secure, maintainable, and well-tested code using ,, and SQL.Implement and enhance data quality, governance, and monitoring solutions.Contribute to CI/CD processes, automated deployments, and modern engineering practices.Collaborate closely with cloud, security, architecture, and business teams.About the customer: In this role, you will design and build scalable data pipelines, data products, and backend services using Azure Databricks, Apache Spark, PySpark,, and SQL. You will contribute to a modern cloud-based data architecture and help deliver reliable, high-performance data solutions.Framework;
Location: Zurich, SwitzerlandStart Date: ASAP (flexible for the right candidate)Contract Duration: 12 months, with possible extensionWork Model: Initially 100% onsite in Zurich during onboarding, followed by a hybrid setup (60% onsite / 40% remote within Switzerland)Requirements: 5+ years of professional experience in Data Engineering, including building enterprise-scale data platforms and ETL/ELT solutions.Strong hands-on experience with Apache Spark, PySpark, and/or Spark Streaming (must be clearly demonstrated in your CV).Proven experience working with Azure Databricks and large-scale data processing.Excellent programming skills in
and SQL, including SQL performance optimization and troubleshooting.Experience with Spark SQL, Structured Streaming, and Delta Lake. understanding of data modelling, data warehousing, and modern data platform architectures.Experience with cloud-based data solutions, preferably Microsoft Azure.Familiarity with CI/CD pipelines, automated testing, and deployment practices.Strong analytical and problem-solving skills, with the ability to work independently and collaboratively.Excellent communication skills and experience working in Agile environments.Nice to have:Experience in financial services, particularly Structured Products, Trading, or Capital Markets.Experience with Terraform and Infrastructure as Code (IaC).Knowledge of streaming technologies such as Kafka, Azure Event Hubs, Event Grid, or Apache Flink.Experience with dbt or Data Vault 2.0.Experience providing technical guidance and contributing to architectural decisionsCompensation benefits: A challenging 12-month contract with the possibility of extension.The opportunity to work on a modern Azure Databricks Data Platform within a leading financial institution.Exposure to innovative Data Analytics and AI initiatives.A collaborative environment with experienced engineering, cloud, and architecture professionals.A hybrid working model following the initial onboarding period.A straightforward recruitment process consisting of two interview rounds.Swisslinx AGLöwenstrasse 298001 Zürich
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(Senior) Data Engineer (W/ m/ d) in Dübendorf Arbeitgeber: Experis
Experis ist ein hervorragender Arbeitgeber, der Ihnen die Möglichkeit bietet, in einem dynamischen und internationalen Umfeld zu arbeiten. Mit einem starken Fokus auf technologische Innovationen und kontinuierliche Verbesserung fördern wir eine Kultur der Zusammenarbeit und des Wissensaustauschs, während wir gleichzeitig vielfältige Entwicklungsmöglichkeiten für unsere Mitarbeiter bieten. Bei uns haben Sie die Chance, an spannenden Projekten zu arbeiten und Ihre Fähigkeiten in einem hochmodernen industriellen Umfeld weiterzuentwickeln.