Project Manager

Azure Data ArchitectLocation: Collegeville or Philadelphia, PennsylvaniaCustomer is looking for a pure hands-on Azure Data Architect who recently implemented two Azure projects. Required role expectation: Extensive experience (10+ years) in data engineering, data governance, or cloud data architecture. Ability to architect end-to-end solutions – should be able to share screen and whiteboard during the interview. Work closely with data scientists, engineers, business stakeholders, and cloud teams to translate business requirements into technical solutions. Lead teams, provide mentorship, and guide architectural best practices like medallion architecture data design pattern and modern lake house implementation. Monitor cloud data solutions for performance, scalability, and cost, implementing optimizations to reduce cloud spend and improve efficiency.Required tech skills: Azure certification is mandatory. Strong skills in SQL, Python, Spark, and Azure cloud environment. Designed and maintained conceptual, logical, and physical data models using Erwin. Hands-on expertise with Databricks platform, Unity Catalog, Delta Lake, and lakehouse architecture and streaming platforms like Kafka. Azure cloud proficiency: Strong knowledge of Azure services, particularly: Azure Virtual Machines, Azure Storage, Azure Networking. Azure Data Factory, Azure Data Lake, Azure Synapse. Azure Logic Apps, Azure Function App, Event Grid (for integration). Experience with Azure Resource Manager (ARM) templates or Terraform for infrastructure provisioning. Data integration and migration: Proficiency in data integration techniques and tools. Experience with ETL (Extract, Transform, Load) processes. DevOps and CI/CD: Understanding of DevOps principles and practices. Experience with CI/CD pipelines using tools like Azure DevOps, Jenkins, or similar. Scripting and automation: Build testing and validation strategy. Familiarity in scripting languages like PowerShell or Python.Good to have: Designing and implementing conversational interfaces (conversational BI), data preparation and management, natural language processing (NLP) and query handling proficiency in programming languages such as Java, or JavaScript, Python knowledge in BI tools (e.g., Power BI, Tableau, ThoughtSPot, LookerStudio), and data querying languages like SQL. Strong understanding of NLP, machine learning, AI frameworks, generative AI, and large language models (LLMs). Understanding of Azure Databricks Genie, Hive Meta.