
We are looking for a Data Analytics Engineer to join our Finance Data Warehouse team. You will be responsible for analyzing business requirements and data, building data models, aggregates, pipelines and integrations; and developing metrics, reports and dashboards in the Finance and Commerce domain.
β
As a Data Analytics Engineer for the Finance Data Warehouse team, you will be much more than a data expert, you will actively contribute to shaping the future of mobility. You will empower the organisation with scalable, reusable, high-quality data products.
β
Designing, building and optimizing elements of Boltβs Finance data platform
Integrating data flows and processes with ERP, Finance systems and 3rd party solutions
Analyzing, understanding and documenting business logic and data structures
Implementing data models and metrics in Data Warehouse including metrics, reports and dashboards in BI platform
Proactively solving technical and business challenges and fixing bugs
Work independently and together with stakeholders (Product teams, Data Platform, Finance) to improve data infrastructure, pipeline and reporting environment
β
β
A university degree in a technical subject (Computer science, Mathematics or similar)
Proficient in SQL (MySQL, PostgreSQL, SparkSQL etc.) and data modeling. Extra credit from hands-on experience in distributed data processing (Spark or similar), working with cloud systems (AWS, Azure, Google) and operating with modern data stack tools like dbt, airflow, fivetran etc.
At least 2-4 years of experience in data engineering or analytics engineering with solid knowledge of algorithms, data architectures and database design (OLTP/OLAP) and experience with BI tools such as Looker or PowerBI
Good English and communication skills, willingness to experiment, learn and grow
Competency and experience at least with 1 programming language like Python and strong understanding of engineering best practices (version control, testing, CI/CD)
Keen to understand business logic, analytical skills to design solutions for business. Previous understanding of accounting and financial data, analytics and integrations is beneficial
β