Scale Marketing is seeking a Data Engineer to build, enhance, and maintain the infrastructure that powers data-driven decision-making across client accounts, turning raw data into actionable insights that drive business value.
Requirements
- 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.
Responsibilities
- 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.
Other
- 23+ years of professional experience in Data Engineering, ETL development, or related roles.
- 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.
- In office Tuesday-Thursday, in our Chicago office
