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Job Description Architect, Data Platform Engineering Location: Gurugram (Hybrid) Experience: 12+ Years Employment Type: Full-Time Position Summary We are seeking an experienced Architect Data Platform Engineering to lead the implementation and optimization of enterprise-scale data platforms on Azure and Databricks Lakehouse . This is a hands-on architecture role responsible for translating enterprise data architecture into scalable engineering solutions by designing robust data pipelines, implementing governance frameworks, building curated data models, and driving automation through CI/CD and Infrastructure as Code (IaC). The ideal candidate will possess deep expertise in Azure Data Platform, Databricks, DevOps, and modern data engineering practices while providing technical leadership and mentoring engineering teams to deliver high-quality, scalable data solutions. Key Responsibilities Data Engineering & Platform Development Design, develop, and maintain scalable data ingestion frameworks using Azure Data Factory (ADF), Azure Databricks, PySpark, and Spark . Build and optimize Bronze-to-Silver transformation pipelines with integrated data quality checks, schema validation, and data contract enforcement. Optimize data pipelines for performance, scalability, reliability, and cost efficiency. Develop batch and streaming data processing solutions aligned with enterprise standards. Data Modeling & Analytics Design and implement Gold-layer curated data models to support enterprise analytics and reporting. Develop dimensional models including Star Schema, Snowflake Schema, Fact Tables, Dimension Tables, Surrogate Keys, and Slowly Changing Dimensions (SCD) . Ensure reusable and scalable semantic models across business domains. Collaborate with business stakeholders to define KPIs, business rules, and data validation scenarios. Manage schema evolution, backward compatibility, and impact analysis for production data models. DevOps, Automation & Infrastructure Own and maintain CI/CD pipelines using Azure DevOps. Automate project onboarding, repository creation, deployment pipelines, and engineering templates. Implement Infrastructure as Code (Terraform) and automation using PowerShell and Python . Troubleshoot deployment issues, permissions, and pipeline failures while ensuring engineering best practices. Data Governance & Quality Implement enterprise governance standards using Unity Catalog . Enforce metadata management, naming conventions, access controls (RBAC/ABAC), and data governance policies. Build and maintain data quality frameworks, schema enforcement, and metadata-driven architectures. Architecture & Technical Leadership Translate enterprise architecture into detailed technical designs and reusable engineering assets. Develop engineering playbooks, templates, and implementation standards to drive consistency across projects. Promote automation-first engineering practices throughout the platform. Team Enablement & Collaboration Mentor and support engineering teams through design reviews, technical guidance, and troubleshooting. Create reusable assets and documentation to improve delivery efficiency. Partner with architects, business stakeholders, and delivery teams to ensure successful implementation of enterprise data solutions. Required Skills & Qualifications Technical Skills 12+ years of experience in Data Engineering, Data Warehousing, and Enterprise Analytics Platforms . Strong hands-on experience with: Azure Data Factory (ADF) Azure Data Lake Storage (ADLS) Azure SQL Azure Databricks Delta Lake Delta Live Tables (DLT) Apache Spark / PySpark Databricks Workflows Unity Catalog Advanced proficiency in Python (PySpark) and SQL . Experience designing both batch and streaming data pipelines . Expertise in Azure DevOps , CI/CD pipelines, Git repositories, deployment automation, and policy management. Strong experience with Terraform , PowerShell , and Infrastructure as Code (IaC). Knowledge of Microsoft Fabric is highly preferred. Strong understanding of data governance, metadata management, schema enforcement, and enterpris .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.