The Cimpress Business Analytics (Cimba) team is made up of engineers and technologists working in five countries who are passionate about data and making it available for our business partners. Our work involves design and development of systems and tools for data collection, data processing, data correction, monitoring, data access platforms and much more – all of these ultimately at large scale. Insights derived from our processes drive and enable decision making throughout Cimpress.
We are looking for an exceptional, highly driven, hands-on Analytics/Data Engineer to join the Cimba team in Winterthur, contributing to create our Amazon cloud based data processing pipeline, data processing infrastructure as well as decide what, how, and when to collect data from our microservices-enabled mass customization platform (MCP). We’re looking for someone has an interest in analytics, who gets the entire spectrum in the big data analytics continuum, someone who is an engineer by training, and someone who is passionate about taking on the toughest problems in a big data world. You enjoy keeping abreast of the ever-evolving big data landscape and making sense of it through advanced data engineering and rendering techniques and tools, and sure, maybe some classic BI technologies as well.
We are looking for a highly motivated engineer who thinks outside the box, and who is a bit outside the box. The ideal candidate has it all: software engineering skills, a broad familiarity with analytic methods and tools, experience with big data challenges.
You will work with a diverse base of global partners, program leads, architects, other analytics engineers, and business intelligence developers to build a platform that delivers the right data to the right people at the right time. This a critical role that will have a significant impact on the direction of our products, technology and business.
Role and Responsibilities
- Be a member of a high-performance big data analytic platform development team.
- Work directly with stakeholders to understand their requirements, assess the business impact and prioritize work accordingly.
- Build scalable, extendible data pipelines and data models to provide decision-support to Customer Service and Product teams.
- Work closely with other Cimpress teams to understand how source system changes impact our upstream data processing.
- Contribute to early quality activities, including peer reviews of estimates, designs and code.
- Contribute in building, improving and maintaining a high performance and highly scalable data pipeline to collect and process billions of events per day.
- Work with real-time data processing and streaming techniques and workflows.
- Evolve data processing pipeline that collects, connects, centralizes, and curates data from various data sources.
- Work directly with stakeholders as necessary to understand requirements, assess the business impact and prioritize work accordingly.
- Contribute in building a distributed data store that will be central source of truth and help shape architecture to propagate relevant data to various warehouses.
- Research and assess the viability of the latest processing and data storage technologies.
- A graduate from a top-tier university, and hold a Bachelors computer science or related technical field.
- 0 - 3 years of experience in Analytics Engineering or related discipline.
- Experience with a big data analytics platform or analytics-focused role a plus.
- Demonstrated skill in any of : Java, Scala, Python, Go, NodeJS
- Familiarity with big data technologies – Apache Spark, Kafka, Redis, etc. and their equivalent cloud based managed service offerings.
- Additional familiarity with serverless computing concepts and frameworks as provided by the major cloud providers.
- Intermediate SQL knowledge required, including subqueries, UDFs, windowing functions demonstrated in at least one major database.
- Knowledge of both SQL and NoSQL databases: relational (SQL Server, incl. T-SQL, Scripting, etc.); columnar (AWS RedShift, Vertica); noSQL (MongoDB, Redis, Cassandra - key-value stores, graph databases); large-scale MPP databases: Vertica, Greenplum, Redshift; Hadoop, HBase, Hive, Presto.
- Experience of predictive models, classification techniques, and clustering algorithms a plus.
- Understanding of data flows, data architecture, ETL and processing of structured and unstructured data.
- You thrive in a fast-paced results-oriented data-driven company, and given context, you're capable of self-direction when solving difficult problems in creative ways and making a real impact to the business.
- Software experience preferred, must be comfortable working in an open, highly collaborative team environment.
- Ability to take ownership and get things done in an Agile team setting.
- You have a passion for keeping up with the emerging big data analytics technical landscape.
- Experience with agile (e.g., Scrum) or lean (e.g., Kanban) methodologies and practices.
- Contribute in building creative solutions for processing low-latency high-volume data.