Informacje o stanowisku

The Analytics Engineers goal is to manage the entire data value chain, from data sources to business insights.
An Analytics Engineer is responsible for collecting business requirements, modeling data, building data pipelines, creating data visualizations, and helping businesses make decisions based on this data. You can use various technologies covering the full data life cycle and work with different kinds of datasets.
An Analytics Engineer often understands both business and technology and is a good communicator who can help them understand each other. He/she can turn business requirements into working data products (like reports and analysis), often in cooperation with different stakeholders.

• 3+ years of experience working with Looker
• Being familiar with at least one programming language (preferably Python)
• Proficiency in SQL and at least one DBMS (e.g., BigQuery, Hive, Oracle)
• Ability to map business requirements to data products (reports, analysis)
• Experience at designing and defining data structures and relationships tailored for analysis that align with business requirements (also taking into account efficient storage retrieval)
• Ability to work with different datasets and data sources
• Being familiar with data visualization best practices and the ability to tell stories with data
• Experience working with dbt and FlinkSQL in a plus

The Analytics Engineers goal is to manage the entire data value chain, from data sources to business insights.
An Analytics Engineer is responsible for collecting business requirements, modeling data, building data pipelines, creating data visualizations, and helping businesses make decisions based on this data. You can use various technologies covering the full data life cycle and work with different kinds of datasets.
An Analytics Engineer often understands both business and technology and is a good communicator who can help them understand each other. He/she can turn business requirements into working data products (like reports and analysis), often in cooperation with different stakeholders.

,[Collecting business requirements for data solutions (reports, analysis), Advising on metrics for business performance monitoring, Monitoring, building data pipelines, and implementing data transformations (mostly in SQL), Designing and implementing data model in a BI tool, Building reports and dashboards, Data validation and testing, Communicating results to the business and helping to use them to make decisions, Data literacy knowledge sharing, Staying up to date with the latest trends and best practices in analytics engineering Requirements: Looker, Python, SQL, BigQuery, Hive, Oracle, FlinkSQL 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.

Praca Warszawa

Warszawa - Oferty pracy w okolicznych lokalizacjach