Data Solutions Engineer — BI, Dashboards & Data Modeling

Edged

United States

On-site

USD 120,000 - 170,000

Full time

2 days ago

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Benefits offered by this job

Medical benefits

401(k)

Paid holidays

PTO

Job summary

Edged is seeking a data modeling/BI specialist to design, develop, and maintain data models and reports for a global data platform supporting analytics and operations. You will collaborate with analysts and engineers to ensure governance, quality, and scalable data solutions across ERP, CRM, and work order systems.

The role requires 4–6 years of data warehousing experience, knowledge of Power BI, and hands-on work with Fabric/Synapse/Snowflake.

Qualifications

4-6 years of experience in data warehouse data modeling, database design, or data architecture.
Degree in Information Systems, Computer Science or equivalent degree or experience.
Experience in report writing and visualization design using industry-standard tools.
Experience with data warehouse solutions such as Fabric, Synapse or Snowflake.
Experience working with relational databases (SQL Server, PostgreSQL, MySQL) and/or NoSQL databases (MongoDB, Cassandra, DynamoDB).
Experience working with data from a combination of ERP, CRM, or work order management systems.
Understanding of data governance, security, and compliance standards (GDPR, HIPAA, etc.).

Responsibilities

Design, develop and maintain data models supporting business intelligence, analytics, and operational needs.
Design, develop, maintain and document reports (paginated and interactive visualizations) as standard product offerings, ensuring consistent availability throughout the enterprise.
Work closely with business analysts and stakeholders to understand data requirements and translate them into effective solutions.
Define and enforce data standards, governance policies, and best practices for data architecture.
Collaborate with IT and engineering teams to ensure seamless integration of data models from data pipelines, warehouses, and analytical solutions.
Maintain data dictionaries, metadata repositories, and documentation for data models.
Identify and resolve data quality and consistency issues across different systems.
Identify and track tasks and milestones to maintain and enhance data products and report progress and issues to IT and business leadership.