Data Analyst, DWH | Client-Facing Contract in Italy

Linkedin; Emilia-Romagna; In loco; EUR 42.000 - 66.000; Tempo pieno

Descrizione del lavoro

Linkedin is seeking a Data Analyst (Contract) to work with clients and internal teams to understand business needs, analyze data, define data mappings, and ensure the accuracy and quality of data within the Data Warehouse environment in the Bologna area.

The role involves leading client discussions, performing data profiling and validation, maintaining KPIs and data definitions, and collaborating with Data Engineers to resolve issues, while mentoring teammates to uphold high data standards.

Competenze

• 5+ years experience as a Data Analyst or DWH Analyst.
• Experience leading client discussions to translate goals into data requirements.
• Strong MSSQL, T-SQL experience and data profiling skills.
• Ability to define business logic, KPIs and data definitions.
• Excellent communication and stakeholder management.

Mansioni

• Lead client discussions to translate goals into data requirements.
• Analyze business requirements and map data from sources to the Data Warehouse.
• Present insights and explain data structures to clients.
• Perform data profiling, validation, and ensure data correctness.
• Define and maintain KPIs and data definitions.
• Collaborate with Data Engineers to resolve data issues.
• Mentor team members and promote high data analysis standards.
• Propose data-driven improvements to clients' processes.

Conoscenze

Data analysis

SQL

Data mapping

Client communication

DWH knowledge

Mentoring

KPIs definitions

Data profiling

SQL Server

Stakeholder management

Strumenti

Microsoft SQL Server

T-SQL

Descrizione del lavoro

Linkedin is seeking a Data Analyst (Contract) to work with clients and internal teams to understand business needs, analyze data, define data mappings, and ensure the accuracy and quality of data within the Data Warehouse environment in the Bologna area.

The role involves leading client discussions, performing data profiling and validation, maintaining KPIs and data definitions, and collaborating with Data Engineers to resolve issues, while mentoring teammates to uphold high data standards.