Architect - Data Engineering

5 hours ago

Chennai Thiruvananthapuram, India Guidehouse Full time ₹ 12,00,000 - ₹ 24,00,000 per year

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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