Data Engineer at Jobgether

, , Switzerland -

Full Time

Start Date

Immediate

Expiry Date

03 Sep, 26

Salary

0.0

Posted On

05 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Sql, Python, Airflow, Apache Spark, Data Modeling, Data Pipeline Design, Distributed Systems, Data Governance, Data Quality Monitoring, Kubernetes, Containerization, Infrastructure As Code, Real-time Data Streaming, Data Observability, Cloud Infrastructure, Analytical Thinking

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineer in Switzerland. Join a forward-thinking engineering team at the forefront of building the data foundation for next-generation AI and cloud technologies. In this role, you will design and maintain scalable data infrastructure that powers analytics, reporting, and strategic decision-making across a rapidly growing technology platform. Working with large-scale datasets and modern data engineering tools, you will help improve data accessibility, quality, and performance while enabling teams across the organization to make data-driven decisions. This is an excellent opportunity for an engineer who enjoys solving complex data challenges, optimizing distributed systems, and contributing to innovative products with global impact. You'll collaborate closely with technical and business stakeholders in a dynamic, international environment that values ownership, learning, and continuous improvement. \n Accountabilities Design, develop, and maintain scalable and reliable data pipelines that support analytics, reporting, and operational business needs. Build and optimize data infrastructure to efficiently process, store, and manage large-scale datasets. Implement data quality monitoring, validation frameworks, and observability practices to ensure accuracy and reliability. Optimize data storage architectures, processing workflows, and query performance across diverse data environments. Design and maintain data models that support analytics, business intelligence, and reporting use cases. Develop automation tools and engineering solutions that improve team productivity and streamline data operations. Ensure compliance with data governance, security, and privacy standards while maintaining best practices for data management. Collaborate with product, engineering, and business teams to align data initiatives with organizational goals. Participate in on-call rotations and provide operational support for production data systems when required. Requirements 3+ years of experience in data engineering, data platform development, or a related technical field. Strong proficiency in SQL and solid programming skills in Python. Hands-on experience designing and maintaining data pipelines using orchestration tools such as Airflow, Prefect, Dagster, or similar platforms. Experience working with distributed data processing frameworks, including Apache Spark or equivalent technologies. Strong understanding of data modeling principles, data architectures, and modern storage systems. Ability to optimize data workflows, processing performance, and large-scale data infrastructure. Familiarity with data governance, data quality, and data lifecycle management best practices. Strong analytical thinking, problem-solving abilities, and attention to detail. Excellent collaboration and communication skills with the ability to work effectively across technical and non-technical teams. Experience with real-time data streaming technologies is considered an advantage. Familiarity with Infrastructure as Code tools, containerization technologies, and Kubernetes is a plus. Knowledge of data privacy regulations, compliance frameworks, and data observability tools is beneficial. Willingness to participate in technical assessments and coding interviews as part of the hiring process. Benefits Competitive compensation package. Flexible remote working opportunities and strong work-life balance. Career growth, mentorship, and continuous learning opportunities. Exposure to cutting-edge AI, cloud infrastructure, and large-scale data engineering projects. Collaborative, innovative, and highly technical work environment. Opportunity to work alongside experienced international engineering teams. Meaningful ownership of projects and the ability to make a visible impact. Dynamic culture that encourages bold thinking, innovation, and professional development. Access to global teams and cross-functional collaboration opportunities. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1

Responsibilities

Design, develop, and maintain scalable data pipelines and infrastructure to support analytics and operational business needs. Implement data quality frameworks and optimize storage architectures to ensure reliable data-driven decision-making.