О компании
SMG Swiss Marketplace Group is Switzerland's pioneering digital hub. Our multinational experts shape the future of our marketplaces to simplify people's lives and drive our customers' success. Our exciting portfolio currently spans four business areas and includes Real Estate, Automotive, General Marketplaces, and Finance and Insurance.
Задачи
•Build data tools used across the company and across different data domains.
•Design and develop data integration pipelines for collecting, storing, and transforming data assets in the data lake and DWH using GCP-native tools and technologies.
•Ensure the reliable operation and maintenance of data infrastructure, including cloud infrastructure orchestration, documentation, data quality checks, and operational efficiency.
•Contribute to building and improving data products, including transformations, dashboards, and logical data warehouse models.
•Support initiatives around personalisation, targeting, experimentation, and data activation across marketing channels.
•Collaborate with analytics, product, and ML teams to enable end-to-end data workflows and create ML-ready datasets.
•Optimise cost-performance trade-offs across GCP services and implement efficient partitioning, clustering, and storage practices in BigQuery.
•Set up data pipelines between the Data Lake and Customer Data Platform, providing real-time data for personalisation and automated communication between our business and users.
•Validate, track, and integrate data from different sources to create scalable, easy-to-understand analytics applications.
•Help build the Automotive data platform of the future and deliver solutions that make a meaningful impact on the business.
Требования
•A bachelor's degree in Engineering, Computer Science, Management Information Systems, or an equivalent field.
•5+ years of hands-on experience working with cloud platforms, preferably GCP, covering data ingestion, processing, warehousing, monitoring, orchestration, and modelling.
•Strong proficiency in SQL and Python, with solid analytical skills to support robust data engineering solutions.
•Hands-on experience building data pipelines using tools and technologies such as dbt, Cloud Functions, and Kafka Streams.
•Good knowledge of DevOps best practices and the automation of documentation, testing, building, deployment, configuration, and monitoring.
•An understanding of cloud-based integration platforms that connect applications, systems, and data sources; experience with Elastic is preferred.
•A strong understanding of data engineering best practices gained through previous roles.
•The ability to work independently and in decentralised teams.
•You look for opportunities to automate repetitive tasks and continuously improve processes.
•You love learning new things and strive for excellence in your day-to-day work.
•You enjoy working in a team but can also work independently and drive projects from start to finish.
•You are proactive, anticipate problems, and propose improvements before they become blockers.
•You operate with a high level of autonomy and accountability, moving work forward with minimal direction.
•You take ownership of key data initiatives, leading their design and delivery from problem discovery to production rollout, and demonstrate seniority through execution.
•You are excited by the idea of not just building pipelines but also shaping how the entire company thinks about data.
Будет плюсом
•Experience with Elastic is preferred; knowledge of this approach is an advantage.
Условия
•Hybrid work environment, and 25 vacation days per year.
•Private health insurance.
•Lots of team activities and perks.
•Free LinkedIn Learning & yearly budget for your personal development.
•Profit Growth Scheme.
•Company Phone (iPhone or Android).
•Cozy office space, with 80 parking spots.
•Great equipment, competitive salary and a variety of fringe benefits like a gym membership and discounts at local stores.
•International team and working environment of talented and fun people.
•Stimulating work experience that will allow you to grow both professionally and personally.
