Data Engineer

Location: Chicago, IL Salary: $ USD Annually - $ USD Annually Description:
We're looking for a Data Engineer III who doesn't just build pipelines - they engineer the bloodstream of the business. Someone who sees a messy data flow and instinctively starts mapping out how to make it cleaner, faster, more resilient. Someone who gets a spark in their eye when they hear "complex integration," "performance bottleneck," or "we need this to scale."

This is a senior-level role for an analytical, solution-oriented engineer who thrives in environments where the data never sleeps. You'll design and optimize pipelines, build integrations that hum, and architect systems that keep our reporting and operations running smoothly. You'll be the person who steps into a broken workflow, traces the issue like a detective, and leaves behind something stronger than what existed before.

You'll work independently, collaborate across teams, and drive improvements that ripple across the entire company.

Where You Sit

Under the department director, you'll partner closely with Data Engineering, QA, and business stakeholders. You're the engineer people trust when they need clarity, stability, or a fix that actually sticks.

Key Responsibilities
Data Engineering

• Pipeline engineering - Build and maintain ETL workflows that scale without cracking under pressure.
• Advanced SQL tuning - Write SQL that slices through massive datasets with precision and speed.
• Automate complex workflows using Azure & Fabric, Spark, and Python.
• Lead engineering efforts on machine learning and AI initiatives - from data prep to deployment.

Integration Development

• Build and maintain SOAP and REST APIs that move data cleanly across internal and external systems.
• Work directly with vendors to ensure integrations stay healthy, accurate, and future-proof.

Operational Support

• Monitor and troubleshoot pipelines like a hawk - ensuring uptime, reliability, and smooth data flow.
• Identify bottlenecks before they become outages and engineer long-term fixes.

Collaboration

• Manage and prioritize work through the ticketing system.
• Communicate clearly in stand-ups and stakeholder meetings.
• Participate in code reviews to uphold engineering standards.
• Contribute documentation that future engineers will actually appreciate.

End User Support

• Provide Tier 3 support for integrated systems (reporting, accounting, and more).
• Partner with business owners to identify improvements and gather requirements.

Leadership & Mentorship

• Mentor teammates through knowledge-sharing, training sessions, and hands-on guidance.
• Own complex projects end-to-end, delivering solutions aligned with business goals.

Required Experience & Qualifications

This is a senior (Tier III) role requiring deep experience in data engineering.

• Bachelor's degree in Computer Science, Information Systems, or equivalent experience.
• Expert knowledge of SQL, dbt, Python, and/or C#.
• Expert experience with orchestration tools like Azure Data Factory.
• Strong understanding of data modeling and ETL concepts.
• Experience with Git and version control best practices.
• Independent problem-solver with the ability to untangle complex technical challenges.

Typical Behaviors & Working Style

The ideal candidate:

• Adapts quickly and flexes to meet the needs of the moment.
• Maintains a people-oriented, service-driven mindset - even when reserved.
• Makes decisions collaboratively but carefully, relying on proven processes and established knowledge.
• Communicates clearly and directly based on the technical task at hand.
• Leads through expertise, owning quality and following up closely when delegating.

Preferred Working Environment & Job Characteristics

You'll thrive here if you enjoy:

• A complex, senior-level engineering environment with high expectations for independence.
• A reliability-focused setting where uptime, performance, and data integrity matter.
• A fast-paced workload balancing delivery, operations, and cross-team collaboration.

You'll find satisfaction in:

• Solving deep technical problems and improving system performance.
• Building automation that eliminates repetitive work.
• Leading through expertise and raising the bar for engineering standards.

What Success Looks Like

• Pipelines and integrations run reliably at scale, powering critical systems and analytics.
• Operational issues are resolved proactively with minimal downtime.
• The data engineering function grows stronger through documentation, quality delivery, and ownership.

Working Conditions

This is a remote role. All required technology will be provided.

Training Includes

• Remote orientation (live + recorded sessions).
• IT security training.
• Internal development processes and procedures.
• Company-approved AI tools.

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