Data Engineering Lead

Rewards Network

Data Engineering Lead managing modern data stack at Rewards Network. Leading technical decisions and overseeing data teams in a hybrid work setup.

Posted 7/26/2026full-timeChicago • Illinois • 🇺🇸 United StatesSenior💰 $190,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, including model design, data pipeline monitoring, and technical leadership. Proven ability to mentor teams, enforce architecture standards, and communicate effectively with both technical and non-technical stakeholders.

Highest-signal resume keywords

Data Engineering ExpertiseTechnical LeadershipData Pipeline MonitoringData Modeling StandardsCI/CD for Data Pipelines

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonApache AirflowApache KafkaData ModelingData ObservabilityIncremental PatternsTesting StrategyMLOps ConceptsData Quality ChecksIncident Response

Soft Skills

Clear CommunicationDecision-Making Under AmbiguityMentorshipTeam DevelopmentAccountability

Tools & Technologies

GitLabElementaryMonte CarloRedshiftGBQDatabricks

Certifications & Qualifications

Bachelor's Degree in Computer ScienceEngineering or Related Field

Industry Keywords

Data InfrastructureELT PipelinesStream IngestionData Model RFC ProcessTechnical Authority

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheCloudKafkaPython

About the role

Key responsibilities & impact

Establish and enforce architecture standards that ensure consistent designs that produce repeatable results.
Assess the current state of our data infrastructure — evaluate what needs refactoring, and what should be replaced — then execute on that plan with the team.
Lead the continued build-out of the modern data stack, including ELT pipelines, stream ingestion, transformation logic along with storage and compute — serving as the technical authority when the team needs a decision made.
Hire and develop data engineering talent, grow the team with engineers experienced in modern ELT architectures and develop the existing team members through mentorship, code review, and technical leadership.
Define and maintain the data model RFC process, reviewing proposed changes, enforcing boundary discipline, and ensuring no undocumented changes promote to canonical layers.
Directly lead the data science team, setting priorities, managing workstreams, and translating business problems into clearly scoped DS projects — fostering a culture of accountability, technical rigor, and continuous improvement.
Own data pipeline monitoring and observability, ensuring production pipelines have appropriate alerting, data quality checks, and incident response processes so failures are caught early and resolved quickly.
Provide regular visibility into team progress, architectural decisions, and risks to senior leadership, communicating tradeoffs clearly and escalating when business commitments are at risk.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
6–10 years of experience in data engineering or a closely related discipline
2+ years in a technical lead or staff-level individual contributor role
Familiarity with data science workflows, ML model lifecycle, and MLOps concepts
Expertise in data engineering — including model design, testing strategy, incremental patterns, and layer boundary governance
Experience designing and enforcing data modeling standards in a team environment — not just building models, but establishing the patterns others follow
Demonstrated ability to bring a team along technically — through code review, documentation, mentorship, and setting standards that stick
Familiarity with CI/CD for data pipelines (GitLab or equivalent) — including automated testing, deployment workflows, and environment promotion strategies
Experience with data observability and monitoring — alerting on pipeline failures, data quality degradation, and freshness SLAs (familiarity with tools like Elementary, Monte Carlo, or equivalent)
Strong decision-making under ambiguity — this role requires someone who can move forward with incomplete information and course-correct, not someone who needs consensus to proceed
Clear, direct communicator who can translate technical tradeoffs for non-technical stakeholders
Technical expertise in: Python, Apache Airflow, Apache Kafka, cloud data warehouses (Redshift, GBQ, Databricks)

Benefits

Comp & perks

Comprehensive benefits package, which includes:
Competitive Time Off Benefits: including flexible PTO, 11 company holidays, and parental leave.
Generous dining reimbursement when you dine with our restaurant clients
401(k) plan with a company match
Two medical plan options- Standard PPO or High Deductible Health Plan (HSA with company match for HDHP participants)
Partnership with Rx n Go, offering certain prescriptions for free
Two dental plan options and a vision plan
Flexible Spending Accounts and a pre-tax commuter benefit program
Accident, Critical Illness, and Hospital Indemnity Insurance Plans
Short Term and Long Term disability
Company-paid life insurance and AD&D insurance, supplemental employee, spouse, and child life insurance
Employee Life Assistance Program
Hybrid working environment in a new office space downtown near the Metra Train stations and catered lunches on Tuesdays.