Job Description

Scale Marketing is seeking a skilled and motivated Data Engineer to join our growing team of analytics experts. In this role, you will be instrumental in building, enhancing, and maintaining the infrastructure that powers our data-driven decision-making across client accounts.

You will collaborate closely with Account Executives, Data Scientists, and other cross-functional partners to design and implement scalable data pipelines, ensure high-quality data delivery, and support real-time insights through dashboards and analytics tools.

We’re looking for someone with a passion for big data, deep technical expertise, and a collaborative mindset—someone who can turn raw data into actionable insights that drive real business value.

What You’ll Do

• Design, build, and maintain scalable and reliable data pipelines to support data integration, transformation, and analysis.
  


• Assemble large, complex datasets from multiple sources to meet business and technical requirements.
  


• Develop and maintain robust ETL processes using modern data technologies (SQL, Python, AWS, etc.).
  


• Partner with internal teams (including Account, Data Science, and Leadership) to understand data needs and develop infrastructure solutions.
  


• Create and support dashboards and other data visualizations for internal and client use.
  


• Collaborate with the data team to continuously improve data systems performance, scalability, and reliability.
  


• Identify, analyze, and resolve data quality and integrity issues.
  


• Participate in code reviews, architecture discussions, and cross-team collaboration efforts.
  


• In office Tuesday-Thursday, in our Chicago office
  

Qualifications

• Bachelor’s Degree in Computer Science, Engineering, or a related technical field.
  


• 2–3+ years of professional experience in Data Engineering, ETL development, or related roles.
  


• Strong experience with AWS services (e.g., S3, Lambda, Redshift, Glue).
  


• Proficiency in Python and Shell scripting .
  


• Deep understanding of SQL and experience writing and optimizing complex queries.
  


• Experience with Linux environments and system-level scripting.
  


• Familiar with CI/CD processes , version control (GitHub), and tools like Jenkins and Docker.
  


• Proven ability to build and manage scalable data infrastructure, pipelines, and architectures.
  


• Comfortable with large-scale data lakes or data warehouses.
  


• Ability to troubleshoot data issues and perform root cause analysis for both internal and client-side data processes.
  


• Experience participating in data architecture design and cross-functional data strategy sessions.
  


• Must be authorized to work in the United States for any employer without the need for sponsorship, now or in the future.
  

What We Value

• Honesty & Integrity – We build trust through transparency.
  


• Respect – We treat everyone with dignity and appreciation.
  


• Diversity & Inclusion – We thrive when different perspectives come together.
  


• Accountability – We treat our clients’ businesses as if they were our own.
  

Perks & Benefits

• Comprehensive health, vision, and dental insurance (with generous employer contribution).
  


• Ongoing education and professional development support.
  


• Open, casual work environment with a flexible hybrid work model.
  


• Company-sponsored events and team-building experiences.
  

About Scale Marketing

At Scale Marketing, we bring together media, creative, and analytics expertise to help businesses grow. We analyze customer data and past media performance to uncover opportunities, drive strategy, and deliver measurable results. Our team is agile, transparent, and deeply invested in our clients’ success.

We’re growing fast—and that’s because we treat our clients and each other with respect, curiosity, and care. If you’re passionate about data, thrive in a collaborative environment, and want to make an impact—you might be a great fit.

Ready to make an impact with data?
Apply now and join a team that’s driving smarter decisions with smarter data.

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