Data & Analytics Engineer İş İlanı

Role Description This is a full-time role for an Azure Data & Analytics Engineer located in İzmir. The role will be responsible for designing, implementing, and maintaining scalable data pipelines using Azure technologies and creating Power BI dashboards. Day-to-day tasks include data modeling, ETL processes, data warehousing, and data analytics. The engineer will work closely with other teams to ensure data integrity, performance, and security.

Qualifications Preferably, skills in Data Engineering and Data Modeling Proficiency in Extract Transform Load (ETL) processes Knowledge of Data Analytics, Power BI Familiarity with Azure and cloud-based data solutions is a plus Bachelor's degree in Computer Science, Information Technology, or a related field Strong communication, requirements gathering, and solution design skills with business stakeholders Working English proficiency; presentation and documentation skills Candidate must have; Developed applications using Microsoft Power Apps or built reports using Power BI. Experienced in big data management, preferably using Azure services such as Azure Data Lake, Data Bricks Microsoft Fabric or Synapse Analytics. Experience using MSSQL (serverless SQL). Professional level proficiency in English (C1 and higher). Responsibilities: Building reports using Power BI. Developing and testing automated flows on Azure Power Automate. Developing dashboards and reports to communicate data insights to stakeholders. Designing high-performance semantic layers with Power BI data modeling (Tabular), DAX, and Power Query (M) Managing data source integrations (SQL, API, Excel/SharePoint), gateway/refresh plans, and RLS/OLS security configurations Implementing design principles, usability, and storytelling standards for enterprise reports and dashboards Also candidate will be responsible for; Conduct ad-hoc data analysis (statistical analysis and modeling) to identify patterns and correlations in the data and deep dives to answer business questions and provide recommendations. Collect, clean, and analyze data from various sources, including internal and external databases, to generate insights and identify growth opportunities.