Data Architect
Job in
South Naperville Area, Will County, Illinois, 60564, USA
Listed on 2026-08-22
Listing for:
SCIGON
Full Time
position Listed on 2026-08-22
Job specializations:
-
IT/Tech
Data Engineering, Data Warehousing, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
As a
Data Architect
, you will play a critical role in defining and executing the organization's data architecture strategy. You will ensure data platforms, systems, and frameworks are designed for scalability, performance, security, and business value. This role serves as the primary authority on data architecture, data modeling, warehousing, governance, and analytics, helping drive modernization initiatives and enabling data-driven decision-making across the enterprise.
This position combines strategic leadership with deep technical expertise, ensuring technology investments align with organizational goals and deliver measurable business outcomes.
Responsibilities- Define and maintain the enterprise data architecture strategy, ensuring alignment between business objectives and technical data solutions.
- Serve as the principal architect for enterprise data platforms, with a strong focus on cloud-based data services, ETL/ELT processes, and distributed data architectures.
- Partner closely with engineering, product, and business teams to design scalable data warehouses, data lakes, and high-performance database systems.
- Establish standards for data modeling, metadata management, master data management, and data exchange to ensure consistency across platforms.
- Lead data modernization initiatives, including migration from legacy systems to modern cloud-native data architectures.
- Collaborate with Dev Ops and platform teams to improve data pipeline automation, monitoring, observability, and deployment processes.
- Provide architectural leadership for high-volume transactional and analytical data systems.
- Partner with security and compliance teams to ensure data privacy, governance, encryption, resiliency, and regulatory adherence across the technology landscape.
- Lead architecture and design reviews, mentor data engineers and architects, and promote best practices in modern data engineering.
- Support technology and business leadership in defining data roadmaps, evaluating emerging technologies, and evolving data capabilities to meet changing business needs.
- Drive enterprise-wide data governance initiatives and establish standards for data quality, consistency, and lifecycle management.
- Proven experience designing, implementing, and maintaining large-scale cloud-based data architectures.
- Deep expertise in modern cloud data platforms and services, including data warehouses, data lakes, distributed storage, and analytics platforms.
- Strong experience with data modeling methodologies, including entity relationship modeling and dimensional modeling.
- Extensive knowledge of ETL/ELT design, data integration, transformation frameworks, and pipeline orchestration.
- Hands-on experience with programming and scripting languages commonly used for data processing, such as Python, SQL, Java, or similar technologies.
- Strong understanding of both relational and No
SQL database platforms. - Experience optimizing database performance, scalability, reliability, and data quality processes.
- Excellent analytical, problem-solving, and communication skills, with the ability to bridge technical and business priorities.
- Ability to think strategically while remaining hands-on in architecture and implementation activities.
- Experience designing and managing enterprise data warehouses, data lakes, and analytics environments.
- Familiarity with data integration standards and electronic data exchange processes.
- Experience with business intelligence, reporting, and data visualization platforms.
Experience with technologies similar to the following is preferred:
- Cloud platforms (AWS, Azure, GCP, or equivalent)
- Containerized and serverless architectures
- Infrastructure-as-Code tools
- Relational databases
- No
SQL databases - Data warehouses and data lakes
- Data visualization and business intelligence tools
- Java, Python, Type Script, or similar programming languages
- Modern application frameworks and services
- REST APIs
- JSON and other data interchange formats
- Authentication and identity management solutions
- Source control platforms
- Infrastructure automation and monitoring tools
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