Insight Global Keyword Location Search view all jobs Data Architect - INTL India Pittsburgh, PA Posted 2 days ago Apply Now Job Description Essential Duties And Responsibilities Architecture & Strategy Define and continuously evolve the data architecture across the Digital Products and Platforms Translate business and technical goals into scalable and resilient platform designs. Own and maintain architectural roadmaps, standards, and decision frameworks. Act as the bridge between architects, SME/Analysts, data engineers, and analytics teams to ensure alignment and compliance with platform standards. Data Engineering & Platform Delivery Design and implement modern ELT/ETL pipelines using tools like Spark, Python, SQL, Scala, and cloud-native components (e.g., Databricks). Design AI ready Data Models (e.g., RAG, agent orchestration, multimodal pipelines) with working reference implementations. Build reusable AI components, templates, and accelerators to enable consistent adoption across teams. Implement and optimize scalable, secure, and resilient AI pipelines, aligned with enterprise data and governance standards. Lead PoC-to-production transitions, ensuring operational readiness, observability, and cost controls Demonstrated success designing and deploying RAG architectures, including vector stores, embedding strategies, chunking logic, semantic retrieval, and hybrid search Deep Hands-on experience with at least one of the following Hyperscaler AI /

Data Platforms:

Azure, AWS Design and implement Data Modelling using Relational DB/NoSQL DB's. Proven Hand-on experience in Databricks & Unity Catalog. Manage data ingestion from heterogeneous sources including ERP, CRM, IoT, and third-party APIs. Guide hands-on development of robust, reusable, and automated data flows. Governance, Metadata, and Quality Implement and enforce data governance frameworks including data lineage, metadata management, and access controls. Develop data models (ERDs, dimensional and 3NF) and define canonical data representations. Collaboration & Leadership Review solution designs and provide architectural guidance to engineering teams. Mentor technical staff while fostering best practices and continuous improvement. Collaborate with DevOps to embed CI/CD, version control, and environment automation across the data lifecycle. Continuously assess and improve platform reliability, scalability, performance, and cost-efficienc We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements 8+ years of hands-on experience in data architecture and engineering delivery. Proven success in building modern data platforms on cloud (Azure, AWS, GCP). Deep knowledge of data lakehouse architectures (e.g., Databricks, Fabric). Proficiency with Python, SQL, Spark, and orchestration frameworks. Experience with ETL/ELT tools (e.g., Informatica, Talend, Fivetran) and containerization (Docker, Kubernetes). Strong background in Data Modeling (ERD, star/snowflake, canonical models). Familiarity with REST APIs, GraphQL, and event-driven design. Demonstrated experience integrating AI/ML and GenAI components into data platforms. Exposure to DataOps and DevOps practices for CI/CD and platform automation.

•  Working knowledge of code management and CI/CD systems (Azure DevOps or GitHub).
•  Familiarity with NoSQL databases (e.g., MongoDB).
•  Exposure to IoT Data Standards like Project Haystack, Brick Schema, Real Estate Core.

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