Data Engineer (US, Remote)
Summary
Senior consulting-focused data engineer who assesses client data platforms and recommends improvements to architecture, pipelines, governance, reporting, and AI readiness. Core tech: cloud data platforms (Microsoft Fabric, Databricks, Snowflake), SQL, Power BI, orchestration/CDC.
Role Overview
Key Responsibilities
- Assess data platform architecture, data pipelines, integrations, and engineering practices to identify gaps and improvement opportunities.
- Evaluate data ingestion, transformation, orchestration, and incremental data loading processes.
- Review data quality, governance, lineage, security, and access management practices.
- Assess reporting and analytics capabilities, including Power BI semantic models and data consumption patterns.
- Identify opportunities to improve platform scalability, reliability, maintainability, and performance.
- Evaluate data architecture and engineering practices for readiness to support AI-enabled applications and analytics.
- Communicate technical findings and recommendations clearly to technical teams and business stakeholders.
- Collaborate with cross-functional teams to understand business requirements and align technical recommendations with organizational objectives.
Required Qualifications
- 8+ years of experience in data engineering, data architecture, analytics engineering, or a related field.
- Hands-on experience with modern cloud data platforms such as Microsoft Fabric, Databricks, or Snowflake.
- Strong SQL skills and experience with data pipelines, orchestration, incremental loading, and change data capture (CDC).
- Experience with Power BI and semantic models for reporting and analytics.
- Experience assessing data platforms, identifying technical gaps, and recommending practical improvements.
- Understanding of data governance, data quality, lineage, data classification, and access controls.
- At least 3 years of experience in consulting, technical assessment, or delivery leadership.
- Strong analytical, problem-solving, documentation, and stakeholder communication skills.
Preferred Qualifications
- Experience working with higher education data systems, including student information systems (SIS), admissions/CRM platforms, or learning management systems (LMS).
- Familiarity with data privacy and compliance requirements, including FERPA.
- Experience with identity resolution, master data management, or entity matching.
- Understanding of data architecture for AI-enabled solutions, including retrieval-augmented generation (RAG).
- Familiarity with CI/CD practices for data engineering and analytics.
- Relevant certifications such as Microsoft Fabric (DP-600/DP-700), PMP, or Scrum certifications.