--- title: 'Principal Data Architect - Multi-Cloud (GCP & Azure) at Egen' canonical: 'https://feeny.ai/job/principal-data-architect-multi-cloud-gcp-azure-egen-hyderabad-6f5pbnx1ev56' type: 'job' last_seen: '2026-11-05' --- # Principal Data Architect - Multi-Cloud (GCP & Azure) at Egen - **Company:** Egen - **Location:** Hyderabad, India - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-10-19 - **Last confirmed live:** 2026-11-05 - **Apply:** https://jobs.lever.co/egen/e588df07-2d96-41ac-889d-412e236fe8ef ## Job description We are seeking a Principal Data Architect to define and drive enterprise data architecture, modernization, and governance strategies across complex multi-cloud (Google Cloud Platform and Microsoft Azure) and hybrid environments. This role will design scalable, secure, and high-performing data platforms while partnering with business and engineering leaders to translate strategic objectives into impactful data solutions. A key focus of this role will be spearheading scalable, agent-driven data migration pipelines to transition legacy on-premises data assets to the cloud, setting the technical direction for engineering teams, and actively managing the customer's technical backlog and delivery roadmap. ## Key Responsibilities - Multi-Cloud Lakehouse Architecture: Lead the end-to-end architecture, design, and implementation of scalable Data Lakehouse solutions across Google Cloud Platform (BigQuery, GCS, BigLake, Dataplex) and Microsoft Azure (Azure Synapse Analytics, Microsoft Fabric, ADLS Gen2, Azure Databricks). - On-Prem to Cloud Migration & Agentic Pipelines: Architect and deploy automated, scalable, agent-driven data pipelines (leveraging GenAI agents and metadata-driven frameworks) to orchestrate, validate, and accelerate complex migrations from on-premises legacy warehouses/databases (Oracle, Teradata, SQL Server) to GCP and Azure. - Client Engagement & Advisory: Collaborate directly with customers to understand business goals, data challenges, and technical requirements; translate them into robust architectural blueprints, technical roadmaps, and actionable delivery plans. - Customer Technical Backlog Management: Own and actively manage the customer technical backlog—translating business epics into technical user stories, prioritizing technical debt, defining sprint milestones, and aligning backlog items with business ROI. - Modern Ingestion & Streaming: Design and implement data pipelines supporting both real-time and batch ingestion using modern orchestration (Cloud Composer, Azure Data Factory, Airflow) and streaming/messaging frameworks (Kafka, GCP Pub/Sub, Azure Event Hubs). - Governance & Lineage: Establish and enforce best practices for unified data cataloging, metadata management, automated lineage, and data quality across multi-cloud and on-prem systems using Dataplex, Microsoft Purview, or open-source governance tools. - Security & Compliance: Define and implement robust data security, identity management (IAM / Azure Entra ID), encryption, row/column-level access control, and regulatory compliance standards across clouds. - Team Technical Leadership & Mentorship: Steer the overarching technical direction of engineering teams; establish architectural standards, mentor senior and mid-level engineers, conduct architecture review, and ensure engineering excellence. - Hands-on Delivery & Prototyping: Balance strategic architecture discussions with hands-on solutioning, architectural spikes, Proof-of-Concepts (POCs), and performance tuning of complex multi-cloud distributed workloads. - Cross-Functional Partnership: Partner with enterprise architects, delivery leads, DevOps engineers, and customer stakeholders to drive solution adoption, operational scalability, and long-term platform maintainability Technical Experience & Tooling Candidates should demonstrate hands-on architecture and design experience across the following domains: - Cloud Platforms:  Deep expertise in both Google Cloud Platform (GCP) and Microsoft Azure enterprise data ecosystems. - Processing Engines: Apache Spark, PySpark, Databricks, Azure Synapse / Fabric Spark, GCP Dataproc. - Modern Migration & AI Automation: Building automated, agentic, or metadata-driven data migration pipelines, automated schema conversion, and data validation agents for on-prem to cloud lift-and-shift/re-platforming. - Messaging & Streaming: Apache Kafka, GCP Pub/Sub, Azure Event Hubs. - Orchestration: Apache Airflow, Google Cloud Composer, Azure Data Factory (ADF). - Analytical Storage & Warehouses:  GCP BigQuery, Azure Synapse, Microsoft Fabric, Delta Lake/Parquet. - NoSQL / Cache Storage: MongoDB, Redis, Bigtable, Azure Cosmos DB. - Containerization & Deployment: Kubernetes (GKE and AKS), Cloud Run, Azure Container Apps. - API Frameworks: Python (FastAPI, Flask) for data service endpoints. - Databases & Querying: Advanced SQL validation and extraction from legacy/RDBMS systems (SQL Server, Oracle, PostgreSQL). - CI/CD & Version Control: Git, GitHub, GitLab CI/CD, Azure DevOps, and Infrastructure as Code (Terraform). Required Qualifications & Skills - 15+ years of progressive experience in Software Engineering, Data Engineering, and Enterprise Data Platform architecture. - 5+ years architecting, migrating, and deploying production data platforms across GCP and/or Azure, with proven multi-cloud integration patterns. - Demonstrated track record leading on-premises/cloud to cloud modernization/migration initiatives, including data ingestion, transformation, automated data reconciliation, and cutover strategies. - Experience designing or integrating autonomous, agent-driven, or LLM-augmented data workflows (e.g., automated schema mapping, code conversion, data quality validation agents). - Proven hands-on experience designing and deploying Lakehouse platforms incorporating Medallion Architecture (Bronze/Silver/Gold) and Data Mesh / Data Product principles. - Deep knowledge of multi-cloud data governance, access management, and cataloging (Dataplex, Microsoft Purview, Unity Catalog). - Strong leadership capability in technical backlog management, agile scoping, sprint planning, and setting technical strategy for distributed teams. - Exceptional stakeholder communication skills: capability to articulate architectural trade-offs to C-level executives as smoothly as reviewing code with engineers. ## Preferred Qualifications (Optional / Good to Have) - Multi-cloud certifications: Google Cloud Professional Data Engineer / Cloud Architect and/or Microsoft Certified: Azure Data Engineer Associate / Azure Solutions Architect Expert. - Hands-on knowledge of Snowflake and Databricks - Familiarity with AWS data services (Amazon S3, Redshift, Glue, EMR). - Experience with LangChain, LlamaIndex, or agentic framework integrations in data operations. Education - Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or equivalent practical experience. ## About Egen ## Company Overview - **One-liner**: Egen is a technology services company that helps organizations accelerate value through cloud, data, platforms, and AI. - **Entity Type**: Private (Privately Held) - **Headquarters**: Naperville, Illinois, United States - **Founded**: 2000 - **Founders**: Not publicly available ## Core Business - **Primary industry**: IT Services and IT Consulting - **Target customers**: B2B, enterprise, public sector (state and local governments), and emerging companies across industries - **Mission or purpose statement**: “Help organizations drive action and impact through cloud, data, platforms, and AI.” ## Products & Services Egen offers technology services rather than packaged products. Key service areas include: - **Cloud Engineering**: Architecture, migration, and optimization with a strategic focus on Google Cloud. - **Data & Analytics**: Data platforms, pipelines, and advanced analytics. - **AI & Machine Learning**: AI/ML solutions, including LLM and agentic change enablement. - **Platform Engineering**: Building and scaling internal platforms. - **Salesforce Services**: Implementation and consulting (via parent company SpringML heritage). ## Market Standing - **Valuation/Market Cap**: Not disclosed - **Key Metric**: Annual Revenue of ~$50M (LinkedIn estimate) - **Notable Investors/Partners**: Parent company SpringML; acquired Qarik Group (Oct 2024); strategic partnerships with Google Cloud and Salesforce. - **Growth Signals**: 643 employees (+20% YoY; 700+ specialists globally); named to Inc. 5000 Fastest Growing Companies; earned Great Place to Work Certification. ## Competitive Advantages - **Deep Google Cloud expertise**: Strategic focus and extensive certifications. - **Pragmatic delivery model**: Agile, value-driven approach from incubation to production. - **Social & sustainability impact**: Pro bono projects for nonprofits, disaster relief, and carbon reduction. - **Collaborative R&D culture**: Emphasis on innovation and continuous learning. ## Strategic Focus Egen is prioritizing AI enablement (LLM, agentic change), expanding public sector presence (President of Public Sector Business), and deepening cloud/data foundations for clients. The company also invests in workforce development and sustainability consulting. ## Why Work Here - **Culture**: Certified Great Place to Work; inclusive, diverse, and entrepreneurial environment. - **Flexibility**: Remote, hybrid, and in-office roles depending on location and role. - **Benefits (U.S.)**: Health insurance, wellness programs, discretionary unlimited PTO, competitive parental leave, 4% retirement contributions, employee referral bonuses. - **Benefits (India)**: On-site gym, group insurance, paid leave. - **Career growth**: Mentoring programs, exposure to cutting-edge cloud/AI technologies, and opportunities to work on impactful social projects. ## Sources 1. [egen.ai/company/](https://egen.ai/company/) 2. [linkedin.com/company/egenai](https://linkedin.com/company/egenai) 3. [jobs.lever.co/egen](https://jobs.lever.co/egen) 4. [egen.ai/leadership/](https://egen.ai/leadership/) 5. 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