Data Engineer

The Data Engineer is a member of the Data & AI team, accountable for building and maintaining scalable data pipelines, models, and semantic layers that power analytics, business intelligence, and AI-driven tools across the organization. This role supports structuring data for AI consumption, including developing models and semantic layers used by Microsoft Fabric Data Agents configured as MCP servers, while integrating and centralizing data from multiple sources. This role develops and optimizes data pipelines and workflows, ensures data is reliable and accessible, and partners with cross-functional stakeholders to deliver practical, data-driven solutions. The ideal candidate is strong in data modeling and engineering, with solid collaboration and problem-solving skills.

Data Modeling & Architecture

Design and build data models and semantic layers optimized for analytics, business intelligence, and AI use cases, including supporting Fabric Data Agents configured as MCP servers that expose curated, governed datasets to AI systems.

Design and manage dimensional data models (star/snowflake) within a medallion architecture to support business reporting, analytics, and AI use cases.

Support initiatives to centralize data from multiple systems into a single master dimensional model.

Ensure data structures and models support business intelligence tools and reporting needs, enabling data-driven decision-making across the organization.

Data Engineering & Automation

Develop and maintain efficient, scalable data pipelines for ingestion, transformation, and integration.

Automate workflows and data integration processes using Azure Data Factory, Microsoft Fabric, Logic Apps, APIs, and other relevant tools.

Pipeline & Dataflow Development

Continuously monitor and enhance data pipeline and data model performance to ensure scalability, reliability, and efficiency for both reporting and AI workloads.

Team Collaboration

Partner with the Enterprise Data team, business analysts, and cross-functional stakeholders to translate data and AI requirements into practical solutions.

Support business users in connecting to, consuming, and working with data for reporting and analysis.

Promote a business partner and ownership mindset to the team to prioritize customer service excellence, adaptability and resilience to change and continuous improvement.

Other tasks as assigned

#LI-REMOTE

Pay Range: 105315.00-129891.00 per_year, General Benefits

Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field (or equivalent experience) preferred.

3+ years of experience in data engineering, data integration, or a similar role.

Proficiency in SQL for data extraction, transformation, and management.

Strong programming skills in Python and familiarity with additional languages such as Scala or Java for building data pipelines.

Hands-on experience with Microsoft Azure and Microsoft Fabric for data engineering tasks, including developing and supporting data pipelines and dataflows with automation tools (e.g., Azure Data Factory, Fabric, Logic Apps). DP-600 or DP-700 certification is a plus.

Experience designing and working with dimensional data models (star/snowflake) within a medallion architecture.

Exposure to AI/agent-facing data patterns is a plus, including familiarity with semantic models for AI consumption or Fabric Data Agents configured as MCP (Model Context Protocol) servers.

Proficiency in creating and consuming APIs for data integration, with experience working in cloud-based data environments, particularly within the Microsoft ecosystem.

Demonstrated workflow and business process improvement skills, particularly in data migration and system integration.

Experience supporting business intelligence and analytics teams by preparing and optimizing data for reporting and visualization tools.

Familiarity with both real-time and batch data processing frameworks.

Strong problem-solving skills with a data-driven mindset.

Proficiency with Microsoft Office (Word, Excel, Teams, Outlook, etc.).

Experience using or willingness to learn approved AI/LLM and automation tools is a plus.

Must be flexible and adaptable to the ever-changing market and Lazer Logistics objectives and goals.

Excellent verbal and written communication skills.

Strong ethical and integrity code.

Ability to collaborate and work well in a fast-paced/dynamic team environment.

Commitment to promoting diversity and inclusion with team and vendors.

Ability to seek and navigate through challenges by maintaining optimism, respect, and dedication to Lazer Logistics' overall purpose and core values.