Data engineer & bi analyst
Pubblicato il 06-10-2026 - Stihl in Italia
Data Engineer & BI Analyst
Salary : €101,000 - 123,000 yearly
Azienda : Stihl
Tipo Lavoro : Full Time
Italy
Descrizione Lavoro - Data Engineer & BI Analyst
About Us
As a family-owned company, it’s the people who continue to make STIHL a successful, world-class brand. Since revolutionizing the forestry industry in Germany with the first electric chainsaw in 1926, the STIHL name has remained synonymous with outstanding innovations, high-quality products and comprehensive service.
With competitive compensation, excellent benefits and exciting growth potential, it is a great time to join the STIHL team!
Why You’ll Love Working at STIHL:
- Excellent health benefitsincluding Medical, Dental & Vision Insurance
- Onsite Health & Wellness Centerfor employees and eligible family members
- Company-paid Life InsuranceandShort & Long-Term Disability
- Robust retirement offeringsincluding:
- A fully vestedPension Plan after 5 years
- A401(k)with generous employer match
- Paid time offin addition to 11 Paid Holidays
- A strong culture ofstability, community, and innovation
- Compensation: $101,000-$123,000 per year with premio opportunities and potential for annual merit increases. Actual compensation will depend on experience, qualifications, and internal equity
About You
You are responsible for helping to build and maintain the infrastructure that powers critical business reporting, advanced analytics, and data-driven decision-making across the company. This role requires someone who thrives in complex data environments, solves ambiguous problems with clarity, communicates effectively with both technical and non-technical stakeholders, is curious, resourceful, and eager to learn new tools and systems.
Job Duties & Responsibilities
- Design, build, and maintain reliable data pipelines using Databricks, Delta Live Tables, and Azure Data Factory.
- Structure and manage Power BI semantic models using Tabular Editor and deployment pipelines.
- Diagnose and resolve data issues spanning multiple systems, including ADF, Databricks, and Power BI.
- Apply strong debugging skills to identify root causes of data mismatches, pipeline failures, and performance issues.
- Collaborate with stakeholders across business functions to clarify data needs and communicate technical concepts.
- Contribute to continuous improvement of our data infrastructure, identifying and implementing scalable solutions.
Specifications
- Bachelor’s degree in Computer Science, Information Systems, Statistics, Engineering, or related field preferred.
- 5+ years of experience in a data engineering, BI engineering, or similar technical role.
- Hands-on experience building pipelines with Databricks and/or Azure Data Factory.
- Strong proficiency with Python for data manipulation and transformation.
- Working knowledge of Power BI, including dataset design, relationships, and refresh behavior.
- Experience working in Git-based workflows.
- Demonstrated skill in debugging issues spanning ingestion, transformation, and reporting layers.
- Clear written and verbal communication skills, especially when explaining technical topics to non-technical stakeholders.
- Strong collaboration skills — shares knowledge, coordinates effectively, and communicates blockers early.
- Proven ability to prioritize and problem-solve in ambiguous or high-pressure situations.
- Proactive approach to improving reliability, performance, or maintainability of existing systems.
- Experience in AI, machine learning, or emerging data technologies — especially where they intersect with analytics and reporting.
- Designing and developing AI solutions using common industry cloud platforms such as Microsoft Azure, Databricks, AWS, or Fabric
- Knowledge of Power BI Premium capacity and refresh management.
- Exposure to metadata-driven frameworks and config-based pipeline logic.
- Familiarity with Unity Catalog, Terraform, or other emerging Databricks tools.
- Experience in automation, optimization, and reducing manual overhead in analytics systems.
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