Data Engineer (US, Remote)

Location: Remote, India

Department: Technology

Experience: 8+years

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.