Informacje o stanowisku
An Analytics Engineer is responsible for managing the entire data value chain, from data sources to meaningful business insights. This role includes collecting business requirements, designing data models, building data pipelines, developing visualizations, and enabling data-driven decision-making.
Analytics Engineers work with a wide range of technologies throughout the data lifecycle and manage diverse datasets. They act as a link between business and technology, ensuring clear communication and alignment between both sides. By working closely with stakeholders, they transform business needs into actionable data solutions—such as reports and analyses—that contribute to organizational success.
- Strong proficiency in GCP, with expertise in BigQuery,
- Solid experience with dbt (Data Build Tool), Dataflow, and Data Vault
- Ability to transform and model data using dbt, including creating logical data models and optimizing them for business analytics
- Advanced proficiency in SQL and Python
- Ability to integrate data from various sources, also in streaming mode
- Knowledge of data quality management (Data Quality) and tracking metadata and lineage in data platforms
- Experience with BI tools (e.g., Power BI, Looker) to visualize data is nice to have
- Ability to work with business teams to define and implement analytics use cases
- Ability to communicate and adapt technology solutions to SFGs business needs
An Analytics Engineer is responsible for managing the entire data value chain, from data sources to meaningful business insights. This role includes collecting business requirements, designing data models, building data pipelines, developing visualizations, and enabling data-driven decision-making.
Analytics Engineers work with a wide range of technologies throughout the data lifecycle and manage diverse datasets. They act as a link between business and technology, ensuring clear communication and alignment between both sides. By working closely with stakeholders, they transform business needs into actionable data solutions—such as reports and analyses—that contribute to organizational success.
,[Gathering business requirements for data solutions (reports, analysis), Providing guidance on metrics for monitoring business performance, Overseeing, developing data pipelines, and executing data transformations (primarily in SQL), Designing and implementing data models within a BI tool, Creating reports and dashboards, Validating and testing data, Presenting results to the business and supporting decision-making based on insights, Sharing knowledge on data literacy, Keeping current with the latest trends and best practices in analytics engineering Requirements: GCP, BigQuery, dbt, Dataflow, Data Vault, SQL, Python, Power BI, Looker Tools: Jira, GIT, Jenkins / GitLab, GitLab, Agile. Additionally: Sport subscription, Private healthcare, Flat structure, Small teams, International projects, Team Events, Training budget, Free coffee, Gym, Bike parking, Playroom, Free snacks, Free beverages, In-house trainings, Startup atmosphere, No dress code, Kitchen.
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