Lead Data Architect

Glint Tech Solutions

  • Chicago, Illinois
  • 5 days ago

    Highlights

    Work spans Customer, Loyalty, Search & Browse, Data Integration, and Cart domains, with current focus on brand onboarding, re-architecture, database migrations, and cloud-native consolidation. Modernization and development of an eCommerce platform for a leading enterprise retail client serving millions of omnichannel customers weekly.

    Numbers & Facts

    LocationChicago, Illinois
    Websitehttps://www.glinttechsolutions.com

    Description

    Job Title: Lead Data Architect
    Location: Chicago, IL (Hybrid – 2-3 days onsite)

    Company Overview
    Glint Tech Solutions is a women-owned, global IT staffing and recruiting firm serving enterprise clients across the USA and Canada.

    Project Description
    Modernization and development of an eCommerce platform for a leading enterprise retail client serving millions of omnichannel customers weekly. Work spans Customer, Loyalty, Search & Browse, Data Integration, and Cart domains, with current focus on brand onboarding, re-architecture, database migrations, and cloud-native consolidation.

    Key Responsibilities

    • Design data architecture to support large-scale data processing
    • Integrate new solutions with existing enterprise architecture
    • Lead cross-functional teams and define technical/architectural strategy

    Mandatory Skills

    • 8+ years overall experience, minimum 1 year in a Lead/Architect role
    • 3+ years recent hands-on Azure Data Factory & Synapse experience
    • Data modeling: conceptual, logical, physical
    • Azure Data Lake Storage, Synapse Analytics, Databricks, PySpark
    • ETL/ELT pipeline development and multi-source data integration
    • Data warehousing patterns: star schema, Data Mesh, Lakehouse, Data Vault
    • Advanced SQL (querying, transformation, performance tuning)
    • Metadata and governance integration
    • Python / Python ETL tools
    • Shell scripting (Bash/Unix/Windows) preferred

    Nice-to-Have Skills

    • Elasticsearch
    • Docker, Kubernetes
    • Azure/Databricks certification
    • Strong stakeholder communication, mentoring, and delivery tracking
    • CS/Data Science academic background

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