Data Engineering Jobs in Bolingbrook, IL (NOW HIRING)

General Purpose of Job:

The Director, Data Engineering – Architect is responsible for defining and governing the enterprise data architecture strategy that powers the Quad/Rise Data Stack. This role provides architectural leadership across data ingestion, transformation, storage, governance, security, and activation platforms to ensure scalability, reliability, and long-term sustainability of the organization’s data ecosystem.

This individual serves as the senior technical authority for data platform design, establishing standards, patterns, and frameworks that enable advanced analytics, modeling, business intelligence, and client delivery. The Director ensures that all data systems are architected for performance, interoperability, compliance, and cost efficiency while anticipating future growth and technological evolution.

The role partners closely with Analytics, Information Security, Software Development, Product developers, and executive leadership to align architectural decisions with enterprise strategy and client needs.
Location: 4 days in office, Chicago or Sussex

Please note: This position is not eligible for visa sponsorship, including F-1 visa holders requiring CPT, OPT, or future H-1B sponsorship. Candidates must be authorized to work in the United States without current or future immigration sponsorship.
Employees can be expected to be paid an annualized salary range of $122,040-$170,000 base plus bonus, based on variations in knowledge, skills, experience, and market conditions.

Key Responsibilities:

Enterprise Data Architecture Strategy

Define and maintain the long-term architectural vision for the Quad/Rise Data Stack, including cloud data platforms, pipeline frameworks, governance layers, and integration strategies. Establish scalable, modular, and secure architecture patterns.

Platform & Infrastructure Design

Design and oversee implementation of:

• Enterprise data warehouse architecture
• Distributed processing frameworks
• Real-time and batch data ingestion pipelines
• API and data-sharing architectures
• Metadata management and lineage systems

Ensure architectural consistency across environments (development, staging, production).

Standards & Engineering Governance

Establish enterprise standards for:

• Data modeling and schema design
• Pipeline orchestration
• Code quality and version control
• Documentation and lineage
• Observability and monitoring

Drive adoption of best practices across engineering teams.

Scalability & Performance Optimization

Ensure systems are designed for high availability, resilience, and performance at scale. Lead capacity planning, workload optimization, and cost management initiatives across cloud infrastructure.

Data Governance & Compliance Alignment

Partner with Information Security and Compliance teams to embed governance, access controls, encryption standards, and auditability into architectural frameworks. Ensure designs support regulatory requirements and enterprise risk management policies.

Cross-Functional Collaboration

Work closely with:

• Data Science and Analytics teams to enable advanced modeling and experimentation
• Software Engineering teams to integrate analytics platforms into client-facing solutions
• Product teams to translate business requirements into scalable technical designs

Act as the architectural liaison between business stakeholders and technical teams.

Technology Evaluation & Innovation

Continuously evaluate emerging technologies, tools, and methodologies to enhance platform capabilities. Lead proof-of-concept initiatives and guide build-versus-buy decisions.

Organizational Leadership

Mentor senior engineers and managers. Develop architectural talent within the Data Engineering function. Influence technical direction without direct ownership of all implementation teams.

Executive Communication

Provide architectural roadmaps, risk assessments, and investment recommendations to executive leadership. Translate complex system design concepts into business-aligned strategy discussions.

Education:

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field required.
Master’s degree preferred.

Experience:

Minimum of 10+ years of experience in data engineering, distributed systems, or enterprise data architecture.

Minimum of 5+ years designing large-scale cloud-based data platforms.

Demonstrated experience leading architectural strategy across multiple teams or business units.

Experience in media, marketing analytics, or high-volume consumer data environments is a plus.

Certificates, Licenses, Registrations:

Preferred certifications:

• Cloud Architecture Certification (AWS, Azure, or GCP)
• Snowflake Architect Certification
• Certified Data Management Professional (CDMP)
• TOGAF or equivalent enterprise architecture certification

Knowledge, Skills & Abilities:

Deep knowledge of:

• Cloud-native data architectures
• Lakehouse and warehouse platforms
• Distributed computing (e.g., Spark)
• Data orchestration frameworks
• API-driven data integration
• CI/CD for data platforms
• Strong understanding of data lifecycle management and system interoperability.
   

Technical Language/Platform: T-SQL, PySpark, Snowflake, cloud-native services (AWS/Azure/GCP), orchestration tools, infrastructure-as-code frameworks.

Systems Thinking: Ability to design cohesive systems across multiple technologies and teams while balancing performance, cost, risk, and scalability.

Leadership & Influence: Proven ability to influence technical strategy across cross-functional teams without direct reporting authority. Strong mentorship capabilities.

Communication Skills: Exceptional ability to communicate architectural vision, tradeoffs, and risk clearly to technical and executive stakeholders.

Organizational Skills: Ability to manage multi-year roadmaps, platform migrations, and complex modernization initiatives.

Strategic Orientation: Forward-thinking mindset with the ability to anticipate scaling challenges, emerging technologies, and evolving business requirements.

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