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Lead Data Architect

Glint Tech Solutions LLC
Posted 16 hours ago, valid for 22 days
Location

Chicago, IL, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • The Lead Data Architect position at Glint Tech Solutions in Chicago, IL, offers a hybrid work model with 2-3 days onsite per week.
  • The role involves modernizing and developing an eCommerce platform for a major retail client, focusing on various domains including data integration and database migrations.
  • Candidates should have a minimum of 8 years of overall experience, with at least 1 year in a Lead or Architect role, and a salary range of $130,000 to $160,000 annually.
  • Required skills include recent hands-on experience with Azure Data Factory and Synapse, as well as expertise in data modeling and ETL/ELT pipeline development.
  • Nice-to-have skills include familiarity with Elasticsearch, Docker, and Azure/Databricks certification, along with strong communication and mentoring abilities.

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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