Senior Data Analyst (Data & Analytics Operations)

Location: Gothenburg, Sweden

Company

hirify.global operates in connected mobility and digital services, working with large-scale data generated by connected assets.

What you will do

• Partner with business stakeholders to identify analytical needs and translate them into defined projects and deliverables.
• Lead analytics initiatives from requirements gathering through data extraction, transformation, modeling, visualization, and delivery.
• Develop, optimize, and maintain scalable data transformation pipelines and analytical data models.
• Build dashboards, reports, and back-end solutions using Power BI and other visualization platforms.
• Analyze complex, petabyte-scale datasets generated by more than 1.8 million connected assets to identify trends, opportunities, and actionable insights.
• Support self-service analytics users and collaborate with technical teams on data quality, performance, and scalability.

Requirements

• Senior-level experience in Data Analytics, Business Intelligence, or Data Engineering.
• Strong hands-on experience with data extraction, transformation, data modeling, and large-scale data pipelines.
• Advanced Power BI knowledge, including dashboard development, reporting, and visualization best practices.
• Experience gathering requirements and translating business needs into technical solutions.
• Ability to independently manage analytics initiatives from concept to delivery.
• Strong analytical thinking, problem-solving, and communication skills.
• Experience collaborating with business stakeholders and cross-functional engineering teams.
• Excellent English communication skills.

Nice to have

• Experience with Databricks, AWS Glue, AWS Athena, Microsoft Fabric, or advanced Power BI use.
• Experience with large-scale or petabyte-level datasets and self-service BI solutions.
• Background in connected vehicles, IoT, automotive, or digital services.

Culture & Benefits

• Cross-functional collaboration with Data Scientists, ML Engineers, Platform Engineers, Data Engineers, and business stakeholders.
• Hands-on ownership of the full analytics lifecycle.
• Continuous improvement of analytics processes, tools, and methodologies.