Data Engineer

🇮🇳Remote - India₹1.2M–₹2.4M/yri24min ago

Higher Ed Data & Analytics Data Engineering Cloud Computing Business Intelligence Higher Education Data Architecture

Role Snapshot

This remote Data Engineer role assesses modern cloud data platforms and provides recommendations on architecture, engineering practices, governance, reporting, and readiness for AI-enabled solutions. The work helps organizations improve data reliability, scalability, and decision-making.

Key Responsibilities: The engineer evaluates data pipelines, ingestion, transformation, orchestration, and CDC processes, reviews governance and security practices, and assesses Power BI semantic models. They communicate findings and practical improvements to technical and business stakeholders.

Skills & Tools: Strong SQL and hands-on experience with Microsoft Fabric, Databricks, or Snowflake are required, along with Power BI, data governance, and data quality expertise. Clear analytical, documentation, and stakeholder communication skills are essential.

Qualifications: Candidates need 8+ years in data engineering, data architecture, or analytics engineering, including at least 3 years in consulting, technical assessment, or delivery leadership. Certifications such as Microsoft Fabric DP-600/DP-700, PMP, or Scrum are preferred.

Location: Remote - India

Compensation: ₹1.2M–₹2.4M/yr (estimated)

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Job Description

Role Overview

We are seeking an experienced Data Engineer to assess and provide recommendations for modern data platforms, helping organizations improve data architecture, engineering practices, governance, reporting, and readiness for AI-enabled solutions.

The ideal candidate combines strong technical expertise in cloud data platforms and data engineering with the ability to evaluate existing environments, identify improvement opportunities, and communicate recommendations to technical and business stakeholders.

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.