Data Engineer & AI Strategist

Eliassen Group; Richardson (TX); On-site; Confidential; Full time

Benefits offered by this job

Health insurance

Retirement plan

Paid time off

Job summary

Eliassen Group is seeking a Data Engineer & AI Strategist in Richardson, TX, on-site. The role owns the enterprise data model, guides the future-state data environment, and governs the BI layer while shaping the AI integration roadmap.

Responsibilities include building data pipelines, overseeing Azure Fabric or Snowflake deployments, and delivering AI-ready architectures with robust data governance and self-service BI standards.

Qualifications

• 8–12 years of experience in data engineering or architecture.

Responsibilities

• Own and evolve the enterprise data model from initial design through production deployment.
• Architect and manage the Azure cloud environment across development, staging, and production pipelines.
• Serve as SME on Microsoft Fabric or Snowflake, including provisioning and governance.
• Design and maintain data integration pipelines between legacy systems and the new data platform.
• Build and maintain the Power BI reporting layer including models, DAX, datasets, and dashboards.
• Lead AI governance, data quality, and metadata management initiatives.
• Define and enforce data governance standards across ownership, lineage, and access controls.

Skills

Azure

Snowflake

Power BI

SQL

Data Modeling

AI Governance

REST API

Copilot Studio

Python

R

Education

Bachelor's degree

Tools

Microsoft Fabric

Azure Data Services

Job description

On-site in Richardson, TX

Our client seeks a Data Engineer & AI Strategist to own the enterprise data model, lead the future-state data environment, govern the BI reporting layer, and drive the AI integration roadmap. The role will partner with an external consulting firm during a modernization program and serve as the internal authority on data architecture and technology selection. The position will collaborate with business leaders and the Controller of Process Improvement to address data accessibility, accuracy, and reporting needs. The selected professional will treat the data platform as a long-term product and provide clear guidance, challenging recommendations when warranted.

This is a full-time, permanent opportunity, offering a competitive salary and comprehensive benefits package. Qualified applicants must be willing and able to work on a w2 basis.

Salary: $150,000 - $170,000/ yr. w2

JN -072026-108071

Responsibilities

• Own and evolve the enterprise data model from initial design through production deployment.
• Architect and manage the Azure cloud environment across development, staging, and production pipelines.
• Serve as the internal subject matter expert on Microsoft Fabric or Snowflake, including provisioning, configuration, dataflows, and governance.
• Design and maintain integration pipelines between legacy systems such as Atlas, Bar Apps, and Risk Master and the new data platform.
• Ensure an AI-ready architecture with sound schema design, metadata management, and data quality standards.
• Build and maintain the Power BI reporting layer including data models, DAX measures, datasets, dashboards, and deployment pipelines.
• Partner with department heads to gather reporting requirements and translate them into scalable solutions.
• Establish self-service BI standards that enable business users to create reports without engineering bottlenecks.
• Lead development of domain-specific Copilot agents using Microsoft Copilot Studio.
• Guide key AI decisions on model selection, security models, and best practices.
• Develop and maintain AI governance, including responsible use policies, access controls for AI workloads, and quality assurance processes.
• Evaluate AI tools and make recommendations aligned with strategy.
• Translate workflow problems into viable AI solutions as a bridge between the business and the AI roadmap.
• Define and enforce data governance standards covering ownership, lineage, quality rules, access controls, and documentation.
• Maintain the enterprise data catalog through all modernization phases.
• Establish change management processes for schema evolution to protect downstream systems and reports.
• Collaborate with stakeholders on new data solutions and AI capabilities.
• Serve as an internal resource on data architecture, BI design, and AI tooling.
• Communicate status and milestones to IT leadership and business stakeholders.
• Work with IT staff to resolve data-related issues and support end users.

Experience Requirements

• 8–12 years of experience in data engineering, data architecture, or a closely related technical discipline.
• Production-level experience with Microsoft Azure data services, Microsoft Fabric and/or Snowflake.
• Advanced Power BI skills including data modeling, DAX, dataflows, row-level security, and deployment pipelines.
• Professional proficiency in SQL, including complex query optimization and stored procedure development.
• Proven experience designing and implementing enterprise data models.
• Experience integrating data from heterogeneous source systems, including legacy environments.
• Familiarity with REST API design and consumption for data integration.
• Working knowledge of AI/ML concepts, responsible AI principles, and introductory experience with Microsoft Copilot Studio, Claude, or equivalent agent tooling.
• Background with BI tools, Python, R scripting, and building tools to realize value from data.
• Strong problem-solving skills, attention to detail, and ability to work independently and in teams.
• Effective communication with IT staff and non-technical stakeholders.
• Preferred: Microsoft Fabric or Azure Data Engineer certification.
• Preferred: Experience with Snowflake and Cortex.
• Preferred: Experience with Change Data Capture tools such as Debezium or Azure Data Factory CDC.
• Preferred: Insurance or financial services industry background.
• Preferred: Experience serving as a client-side technical owner during a consulting-led modernization engagement.

Education Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.