
Senior Analytics Engineer
3 days ago
- Advanced proficiency in SQL and Python
- Extensive experience in Microsoft Azure and knowledge of Lakehouse platforms - Databricks
- Hands-on experience with dbt
- Experience in data modeling
- 3+ years of experience using BI tools like Power BI
- Experience in processing large datasets, knowledge of query optimization in the Big Data stack
- Interest in areas such as Data Governance, Data Quality, etc., based on both project experience and personal interest in these fields
- Ability to map business requirements to data products (reports, analysis)
- Ability to work with different datasets and data sources
The role of an Analytics Engineer involves overseeing the entire data value chain, spanning from data sources to actionable business insights. This position entails gathering business requirements, designing data models, developing data pipelines, creating data visualizations, and supporting decision-making processes through data-driven insights.
Analytics Engineers work with diverse technologies across the full data lifecycle and handle various types of datasets. They bridge the gap between business and technology, effectively communicating to ensure mutual understanding. By collaborating with stakeholders, they translate business needs into functional data products, such as reports and analyses, to drive organizational success.
,[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: SQL, Python, Azure, Databricks, dbt, Power BI 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.-
Senior Analytics Engineer
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