Data Solutions Engineer And Modeler

Overview

• Collaborate with business teams to capture workflows and define data domains for enterprise data modeling.
• Translate business requirements into logical models ensuring data is mastered and consumable in downstream systems.
• Engage with stakeholders to ensure alignment and usability of data models and outputs.
• Work closely with data engineers and analysts to deliver business-ready data solutions.
• Prototype transformations and pipelines in Python/Databricks for production implementation.
• Maintain logical and semantic data models aligned with enterprise architecture.
• Explore and validate datasets using SQL, Python, and Databricks.
• Ensure data integration patterns meet business requirements and technical standards.

Key Responsibilities & Duties

• Partner with operational leaders to capture workflows, entities, and data requirements.
• Design and maintain logical and semantic data models for core domains.
• Define attributes, hierarchies, and business rules for data domains.
• Collaborate with data engineers on data ingestion, transformation, and enrichment.
• Prototype transformations and pipelines in Python and Databricks.
• Present domain models to stakeholders and iterate based on feedback.
• Ensure data models are accurate, trusted, and usable for business consumption.
• Validate datasets using SQL and Python to shape raw data into domain tables.

Job Requirements

• Bachelor of Science (BS) degree in a relevant field.
• 5–8 years of experience in data architecture or solution design.
• Proficiency in SQL, Python, and Databricks for data modeling and validation.
• Deep understanding of data semantics, ontologies, and master data management.
• Familiarity with data integration patterns and third-party data sources.
• Strong communication skills for translating complex data concepts.
• Organized and proactive with the ability to balance design and prototyping.
• Experience in financial services or consulting is preferred.