Architect - Data Engineering

Guidehouse

10 - 15 years

25 - 35 Lacs

chennai thiruvananthapuram

Posted:3 days ago| Platform:

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Skills Required

data modelling data engineering data architecture azure cloud data warehousing

Work Mode

Work from Office

Job Type

Full Time

Job Description

What You Will Do:

Design and lead end-to-end architecture for modern, cloud-native data engineering, AI/ML and analytics platforms across the full data lifecycle, including ingestion, storage, transformation, and consumption.
Architect high-performance data solutions using Azure Databricks, Fabric, Snowflake, AWS Redshift, Power BI, Tableau, Python, and other relevant technologies.
Collaborate with technology leadership and engineering teams to align solutions with enterprise strategy, business goals, and innovation roadmaps.
Define and enforce standards for data quality, metadata, lineage, and governance in partnership other teams using market leading tools.
Provide architectural guidance for AI/ML integrations, including data preparation, feature engineering, and model deployment support.
Conduct design reviews, architectural assessments, and performance tuning to ensure system reliability, scalability, and maintainability.
Develop and maintain reusable patterns, frameworks, and coding standards in ADF, Python, PySpark, and SQL.
Collaborate with product managers, engineering leads, analysts, and data scientists to deliver high-impact, cross-functional solutions.
Drive the evaluation and adoption of emerging technologies in cloud data platforms, streaming analytics, and intelligent automation.
Mentor data engineers and oversee best practices in solution design, code quality, documentation, and continuous improvement.
Support DevOps and DataOps initiatives by integrating CI/CD pipelines, Git workflows, and automated testing into engineering workflows.

What You Will Need:

Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field.
10-12 years of progressive experience in data engineering, data modelling including at least 5 years in an architecture-focused or lead technical role.
Proven experience architecting enterprise-grade cloud data platforms using Azure (and AWS).
Deep expertise in technologies such as Azure Data Factory, Snowflake, Databricks, Spark/PySpark, and SQL-based processing.
Strong grasp of modern data architecture paradigms including data lakehouse, data fabric, microservices, and event-driven design patterns.
Solid understanding of DevOps and Infrastructure-as-Code practices, including CI/CD pipelines, Docker/Kubernetes, and automated deployment frameworks.

What Would Be Nice To Have:

Familiarity with modern data architecture frameworks, including data mesh, data fabric, and data lakehouse.
Industry experience in Healthcare, Finance or other highly data-driven domains.
Experience with Database Lifecycle Management (DLM) tools and strong understanding of CI/CD pipelines, branching strategies, and collaborative DevOps practices.
Hands-on experience integrating with data governance and master data management platforms s.
Proficiency in Python, Scala, or similar programming languages commonly used in large-scale data engineering.
Understanding of AI/ML model lifecycle architecture, including data preparation, model training, and production deployment best practices.
Relevant certifications in cloud architecture (e.g., Azure Solutions Architect, AWS Certified Data Analytics) or enterprise architecture (e.g., TOGAF Framework

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