Data Engineer

Overview

Position Title: Business Intelligence Analyst

Area of Focus (Sub Team): Data Engineering Specialist

Tigunia Core Values: To produce results, solve your problems with a sense of urgency, treat clients and co-workers with respect, and foster long-term relationships.

Position Description (Abstract):

Tigunia is seeking a technically focused Business Intelligence Analyst with a specialization in data engineering and warehouse modeling. This role is ideal for someone who enjoys building scalable data infrastructure, working with modern data tools, and developing clean, reliable models that power reporting and analytics. While the role is primarily technical, it also includes client-facing responsibilities, including leading smaller engagements and collaborating with stakeholders to ensure solutions meet business needs.

You will work closely with internal teams and clients as a consultant to design and implement integrated data warehouse models, develop transformation logic in Python and SQL, and support reporting platforms like Power BI, Tableau, and Jet Reports. This is a hands-on role requiring strong communication skills, technical depth, and a passion for clean, maintainable solutions.

• Design and implement scalable, integrated data warehouse models incorporating data from Business Central and other sources
• Develop and maintain data pipelines using Python, SQL, and modern ETL tools
• Lead smaller client engagements, including requirements gathering and solution delivery
• Collaborate with reporting specialists to ensure data models support business KPIs and visualization needs
• Define and document transformation logic, data mappings, and warehouse specifications, adhere to modeling standards and governance practices
• Support report development in Power BI and Jet Reports as needed
• Troubleshoot data quality issues and optimize performance of data models
• Use Git Hub for version control, collaboration, and documentation of data engineering workflows

• Strong technical problem-solver with a passion for data architecture and engineering
• Comfortable working independently and managing priorities across multiple projects
• Experienced in client engagement and capable of leading smaller projects
• Detail-oriented and committed to producing clean, well-documented solutions

• 4+ years of experience in data engineering, BI development or related roles
• Experience with ERP data structures and warehouse modeling
• Proficiency in Python and SQL for data transformation and analysis
• Strong experience with Mage.
  
  AI, dbt, Microsoft SQL Server, Snowflake, or Microsoft Fabric
• Experience using Git Hub for version control, collaboration, and workflow management
• Strong understanding of dimensional modeling and the Kimball methodology
• Experience with documentation, versioning, and data governance practices

• Previous experience as a Business Intelligence (BI) Consultant, with strong understanding of analytics and reporting
• Hands-on experience with data governance and metadata management tools, such as:
  Microsoft Purview, Data Hub, Open Metadata, or Apache Atlas
• Familiarity with Microsoft Business Central and its data structure
• Exposure to various reporting platforms such as:
  Tableau, Domo, Sigma, Superset, etc.

• Health insurance for yourself and your family – 100% employer paid for employee and 50% employer paid for dependents
• Dental and Vision insurance for yourself and your family – 100% employer paid for employee and dependents
• Life/AD&D Insurance for yourself – 100% employer paid and covers 100% of your salary
• Short Term Disability for yourself – 100% employer paid and covers 60% of your weekly salary up to $1,750.00
• Long Term Disability for yourself – 100% employer paid and covers 60% of your monthly salary up to $6,000
• 401k with 4% match
• Flex-time and paid time off to promote a healthy work-life balance

Tigunia provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), political affiliation, military service, or other non-merit-based factors.