Analytics Engineer

The Analytics Engineer is responsible for bridging the gap between data engineering and data analytics by maintaining and developing scalable data models and solutions that support finance, B2B, and B2C teams. The role plays a key part in delivering value through modern data stack technologies (including dbt), supporting cloud migration efforts, ensuring data quality, and maintaining the performance of analytical data pipelines.

Responsibilities

Collaborate with stakeholders across departments to design and implement robust data models and BI solutions; Build, test, and maintain data transformations using dbt (data build tool); Implement software engineering best practices for data, including version control, CI/CD, and automated testing; Deliver day-to-day support and project-related tasks for the data and BI infrastructure; Develop and maintain scalable, maintainable, and well-documented data pipelines; Identify and resolve issues across ETL/ELT processes and data pipelines

Requirements

3+ years of experience in Analytics Engineering, BI, or Data Engineering roles; Strong proficiency in SQL, including complex queries and performance tuning; Hands-on experience with dbt for data transformation and modeling; Understanding of data migration to cloud platforms such as AWS (Redshift) or GCP (BigQuery); Familiarity with database design, version control (e.g. Git/GitHub), and CI/CD practices; Experience with ETL/ELT tools (e.g. Airflow, DBT); Strong analytical thinking and problem-solving abilities; Effective communication skills and ability to collaborate across teams; Attention to detail and focus on continuous improvement and data quality; Adaptability to fast-paced environments

Benefits

Annual bonus scheme; 25 days paid leave; 24/7 Employee Assistance Program; Life Insurance; Enhanced Parental Leave policy; Food Allowance; Multisport Card; Both in house and external training programs; Own training dedicated budget (for conferences, courses etc.)