Data Engineer & BI Analyst

STIHL Inc.; Virginia Beach (VA); On-site; USD 101,000 - 123,000; Full time

Benefits offered by this job

Excellent health benefits including M,

Onsite Health & Wellness Center

Company-paid Life Insurance

Disability coverage

Pension Plan after 5 years

401(k) with employer match

Paid time off plus 11 holidays

Job summary

STIHL Inc. is seeking a data engineer to design, build, and maintain robust data pipelines powering critical business reporting and analytics. You will work with Databricks, Delta Live Tables, and Azure Data Factory to ensure reliable data delivery and scalable BI solutions.

The role requires strong Python skills, Power BI expertise, and experience in Git workflows, with opportunities to contribute to AI-driven analytics in a collaborative, fast-paced environment.

Qualifications

• Bachelor’s degree in CS, IS, Statistics, Engineering, or related field preferred.
• 5+ years of experience in 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 with non-technical stakeholders.
• Strong collaboration and proactive problem-solving in ambiguous environments.
• Experience with AI, ML, or cloud data platforms (Azure, Databricks, AWS) beneficial.

Responsibilities

• Design, build, and maintain 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 across ADF, Databricks, and Power BI.
• Debug data mismatches, pipeline failures, and performance issues.
• Collaborate with stakeholders to clarify data needs and explain technical concepts.
• Contribute to continuous improvement of our data infrastructure with scalable solutions.

Skills

Databricks

Python

Power BI

Git

Data engineering

Delta Live Tables

AI/ML awareness

Education

Bachelor's degree in Computer Science, Information Systems, Statistics, Engineering, or related field

Tools

Databricks

Delta Live Tables

Azure Data Factory

Tabular Editor

Terraform

Power BI deployment pipelines

Unity Catalog

Job description

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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 Planafter 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 bonus 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.