Data & Analytics Engineer

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.