Data Engineer 3

Best-in-class benefits for eligible employees, plus a flexible approach with an array of options, expert guidance, and always-on tools that can be personalized to match your day-to-day reality.

What you’ll do

Design, develop, and manage advanced data structures and pipelines with an emphasis on data quality, accessibility, and compliance with privacy and regulatory standards. This role supports business initiatives by optimizing data processes and storage, while acting as a technical resource across the data platform.

• Design and build data architectures and pipelines to standardize, transform, and protect the integrity of data used for business insights
• Maintain data quality across ingestion, processing, and loading, with monitoring and reporting that supports high standards
• Develop ingestion frameworks for multiple data types, including mechanisms to track and report on data quality
• Create accessible data consumption approaches such as APIs, database views, and data extracts for user applications
• Implement data solutions across platforms including Kubernetes, Teradata, and cloud services such as AWS and Databricks
• Select storage platforms based on data sensitivity, privacy requirements, and access needs
• Apply transformation rules and manage data lineage to support change management and help resolve issues
• Collaborate with cross-functional partners to improve data sourcing and processing for quality and efficiency
• Use independent judgment and discretion in matters of significance
• Maintain regular, consistent, and punctual attendance, with the ability to work nights and weekends and follow variable schedules as necessary
• Perform other duties and responsibilities as assigned

What you’ll bring

• Strong SQL proficiency
• Programming proficiency with Python preferred
• Distributed computing experience (for example, Apache Spark)
• Ability to manage cloud data warehouse environments
• Knowledge of at least one cloud provider: AWS, GCP, or Azure
• Familiarity with data pipeline design patterns
• Knowledge of data observability

Tools and technologies you may work with

• SQL, Python, Apache Spark
• AWS, GCP, Azure, Kubernetes, Teradata, Databricks
• dbt, Airflow, Snowflake
• Looker (embedded business intelligence exposure is desired but not required)
• APIs, database views, data extracts
• Data lineage, data observability
• Data Lakehouse Architecture

Experience and education

• 5-7 years of relevant work experience
• Bachelor’s Degree
• Minimum experience: 5 years

How we work

• Understand and apply Operating Principles to guide daily work
• Own the customer experience and act in ways that put customers first
• Know your stuff by learning, using, and advocating technology, products, and services
• Win as a team by working together and staying open to new ideas
• Be an active part of the Net Promoter System by participating in feedback huddles and helping elevate opportunities
• Support a culture of inclusion in how you work and lead
• Drive results and growth and do what’s right for customers, investors, and communities

Salary range: USD 103,643 - 170,271 per year. Location: Chicago, IL (onsite).

This information is intended to describe the general nature and level of work performed. It is not an exhaustive inventory of all duties, responsibilities, or qualifications.