Assess modern data platforms, pipelines, architecture, governance, reporting, and AI readiness. Identify technical gaps and recommend improvements to scalability, reliability, quality, security, lineage, access management, and performance. Evaluate cloud data platforms, ingestion, transformation, orchestration, incremental loading, Power BI semantic models, and analytics capabilities while communicating recommendations to technical and business stakeholders.
Role Overview
Key Responsibilities
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.
- 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.
- 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.
- 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.
Academian Pune, Mahārāshtra, IND Office
Pune, India
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