Data Engineer (Spark, Azure)
We are looking for a Data Engineer who will take a leading role in designing and implementing a scalable enterprise search engine - a platform that provides stakeholders with an intuitive, efficient, and reliable way to query and explore the firm’s data landscape.
Our client is a leading global financial services firm providing wealth management, investment banking, and asset management services to clients worldwide.
This is a hybrid role requiring presence in the client's office in Krakow 3 days a week, with flexible working hours.
Responsibilities
- Design, build, and optimize an internal data search engine
- Analyze datasets and metadata to improve searchability, indexing, and relevance
- Gather and refine search and data discovery requirements with business and IT stakeholders
- Translate business needs into technical specifications and support Agile delivery
- Ensure integration with the broader data ecosystem (data, platform, analytics teams)
- Support testing and monitor search performance, accuracy, and usability
- Prepare analytical reports on data availability and search effectiveness
Requirements
- 3 years + of experience as a Data Engineer, including exposure to large-scale or Big Data environments
- Strong experience with SQL and database systems (relational and NoSQL), including query optimization and schema design
- Strong programming skills in Python and Spark
- Experience with Azure cloud services, including Azure Databricks, Data Lake, and Azure Data Factory, would be beneficial
- Strong communication and stakeholder management skills, with the ability to translate search-related needs into technical solutions
