Data Engineer

Guidehouse Inc.; Chennai; On-site; INR 1,500,000 - 2,300,000; Full time

Benefits offered by this job

Learning & development programs

Job summary

Guidehouse India is seeking a hands-on Data Engineer to build and support enterprise data ingestion pipelines and end-to-end data transformations in a modern data platform. You will implement data quality controls, monitor production pipelines, and collaborate with analytics teams to deliver reliable datasets.

The role requires strong SQL, Python/PySpark skills, and experience with Azure-based platforms and Databricks.

Qualifications

• Hands-on experience building and supporting enterprise data ingestion pipelines and transformations.
• Strong SQL skills and experience with Python, PySpark, or comparable data engineering tools.
• Experience with Azure-based data platforms, Databricks, Microsoft Fabric, or comparable technologies.
• Experience implementing lakehouse architecture and Bronze/Silver/Gold transformation patterns.
• Experience integrating data from databases, APIs, files, and enterprise applications.
• Experience using GitHub, version control, CI/CD, testing, and environment promotion processes.

Responsibilities

• Build and maintain source ingestion pipelines using approved integration patterns for enterprise applications, databases, APIs, and files.
• Develop and maintain Bronze/Silver/Gold transformations using approved frameworks and reusable engineering practices.
• Implement validation and data-quality controls, including completeness, accuracy, consistency, and reconciliation checks.
• Follow GitHub-based CI/CD, testing, release management, and environment promotion processes.
• Monitor production pipelines, investigate failures, troubleshoot issues, and implement corrective actions.
• Support assigned semantic models, including data preparation, refresh dependencies, and troubleshooting in partnership with Analytics.
• Maintain technical documentation, source-to-target mappings, transformation logic, lineage, operating procedures, and job aids.
• Follow established security, access, naming, and development standards.
• Partner with the Principal Data Platform Architect to ensure engineering deliverables align with approved architecture and platform guardrails.
• Collaborate with business and analytics stakeholders to clarify data requirements and deliver reliable, reusable datasets.

Skills

SQL

Python

PySpark

Azure

Databricks

Microsoft Fabric

Power BI

GitHub

Tools

Databricks

Microsoft Fabric

Power BI

Job description

Job Family : IT Architecture/Cloud (India)

Travel Required : Up to 10%

Clearance Required : None

The Data Engineer will build, maintain, and support data pipelines and transformations that enable reliable analytics, reporting, and AI solutions across the enterprise data platform. The role will focus on data ingestion, Bronze/Silver/Gold transformations, data quality, deployment, production operations, assigned semantic models, and technical documentation.

This is a hands-on data engineering role. The Data Engineer will deliver solutions using approved frameworks, architecture patterns, and standards established by the Principal Data Platform Architect, partnering with platform, analytics, security, and business teams.

Key Responsibilities

• Build and maintain source ingestion pipelines using approved integration patterns for enterprise applications, databases, APIs, and files.
• Develop and maintain Bronze/Silver/Gold transformations using approved frameworks and reusable engineering practices.
• Implement validation and data-quality controls, including completeness, accuracy, consistency, and reconciliation checks.
• Follow GitHub-based CI/CD, testing, release management, and environment promotion processes.
• Monitor production pipelines, investigate failures, troubleshoot issues, and implement corrective actions.
• Support assigned semantic models, including data preparation, refresh dependencies, and troubleshooting in partnership with Analytics.
• Maintain technical documentation, source-to-target mappings, transformation logic, lineage, operating procedures, and job aids.
• Follow established security, access, naming, and development standards.
• Partner with the Principal Data Platform Architect to ensure engineering deliverables align with approved architecture and platform guardrails.
• Collaborate with business and analytics stakeholders to clarify data requirements and deliver reliable, reusable datasets.

Required Experience

• Hands-on experience building and supporting enterprise data ingestion pipelines and transformations.
• Strong SQL skills and experience with Python, PySpark, or comparable data engineering tools.
• Experience working with Azure-based data platforms, Databricks, Microsoft Fabric, or comparable technologies.
• Experience implementing lakehouse architecture and Bronze/Silver/Gold transformation patterns.
• Experience integrating data from databases, APIs, files, and enterprise applications.
• Experience implementing data validation, data-quality controls, and reconciliation processes.
• Experience using GitHub, version control, CI/CD, testing, and environment promotion processes.
• Experience monitoring and troubleshooting production pipelines, including failed jobs, refresh issues, and data discrepancies.
• Ability to support assigned semantic models and their upstream data dependencies.
• Ability to maintain clear technical documentation and follow established security, governance, and development standards.
• Strong problem-solving, communication, and collaboration skills.

Preferred Experience

• Experience integrating data from Dataverse, Microsoft 365, Power Platform, ADLS Gen2, or Azure SQL.
• Experience with Databricks workflows, Delta Lake, Unity Catalog, Microsoft Fabric pipelines, or OneLake.
• Experience supporting Power BI semantic models.
• Experience with metadata, lineage, and Microsoft Purview or comparable governance tools.
• Experience working in regulated environments and following established compliance controls.
• Microsoft Azure, Databricks, or Microsoft Fabric data engineering certifications.

Success Measures

• Source ingestion pipelines run reliably and meet agreed delivery schedules.
• Bronze/Silver/Gold transformations follow approved frameworks and produce accurate, reusable datasets.
• Data -quality controls detect issues promptly and support timely resolution.
• Changes follow established GitHub CI/CD, testing, and promotion processes.
• Production pipeline issues are identified, investigated, and resolved within agreed service expectations.
• Assigned semantic models receive reliable data and refresh support.
• Technical documentation, lineage, and job aids remain accurate and current.
• Eng ineering delivery consistently follows security, access, naming, and development standards.

About Guidehouse India

At Guidehouse India, we're redefining what's possible by creating opportunities that change lives. Guidehouse is a global professional services firm that delivers advisory, technology, and managed services to clients across both the commercial and public sectors. Our teams turn bold ideas into solutions that transform industries, strengthen communities, and drive meaningful impact worldwide.

Across our Chennai, Trivandrum, and Gurugram locations, you'll find opportunities where your passion and curiosity help shape what comes next. With cutting edge benefits, innovative learning and development programs, and a people first culture, we empower our people to lead with purpose.

We continue to expand our teams an