Data Engineering Lead — Build Modern Data Stack (Hybrid)

Rewardsnetwork; Chicago (IL); Hybrid; USD 190,000 - 220,000; Full time

Benefits offered by this job

Hybrid work environment

Competitive benefits package

Dining reimbursement

Job summary

Rewards Network is seeking a Data Engineering Lead to drive the modern data foundation and provide technical leadership across data engineering and data science. The role is hands-on with team-building, migration decisions, and a focus on architectural clarity.

The position is hybrid with in-office presence 3 days/week in Chicago. You will shape ELT pipelines, data models, and governance while mentoring engineers and aligning data initiatives with business goals.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).
• 6–10 years of experience in data engineering or related discipline.
• 2+ years in a technical lead or staff-level IC role
• Experience with data science workflows, ML lifecycle, and MLOps concepts
• Expertise in data modeling standards and CI/CD for data pipelines
• Strong ability to lead a team and communicate technical tradeoffs

Responsibilities

• Establish and enforce architecture standards for repeatable results.
• Assess current data infrastructure and plan refactor/replace.
• Lead build-out of modern data stack including ELT pipelines, ingestion, transformation, storage and compute.
• Hire and develop data engineering talent.
• Direct data science team priorities and roadblocks.
• Own data pipeline monitoring and observability.
• Provide regular visibility to leadership on progress, decisions, and risks.

Skills

Data engineering

Team leadership

CI/CD for data pipelines

Data observability

Data modeling

Python

Apache Airflow

Apache Kafka

Cloud data warehouses

Communication

Education

Bachelor's degree in CS/Engineering or related

Advanced degree in technical field

Tools

GitLab

Job description

Rewards Network is seeking a Data Engineering Lead to drive the modern data foundation and provide technical leadership across data engineering and data science. The role is hands-on with team-building, migration decisions, and a focus on architectural clarity.

The position is hybrid with in-office presence 3 days/week in Chicago. You will shape ELT pipelines, data models, and governance while mentoring engineers and aligning data initiatives with business goals.