Data Engineer - Finance AI Solutions

Target • Brooklyn Park, MN

3d • $75,400 - $135,700 • Hybrid

About The Position

The Data Engineer role within Finance AI Solutions at Target focuses on developing and maintaining scalable data solutions that support the company's financial systems and enterprise reporting capabilities. This position is part of an agile engineering team responsible for building reliable data pipelines, developing data services, and delivering high-quality data to enable business insights and operational excellence. The role involves collaboration with engineers, product managers, data scientists, and business partners to create efficient, scalable, and maintainable data solutions, while also fostering technical expertise in cloud technologies and distributed data processing.

Requirements

• 4 year degree in Computer Science, Applied Mathematics, Physics, Information Technology, Engineering, etc. or equivalent industry experience
• 1plus year of software development experience with Big Data technologies such as Spark, Hadoop, or distributed data processing frameworks
• Programming experience with PySpark, Scala, Java, or Python
• Experience with cloud platforms (AWS, GCP, or Azure) and cloud-based data services
• Familiarity with data modeling, ETL development, and data pipeline design
• Exposure to API development using REST or similar technologies
• Experience with SQL and relational or distributed databases
• Understanding of data governance, security, and software development best practices
• Strong analytical and problem-solving skills
• Excellent communication and collaboration skills with the ability to work effectively on cross-functional teams

Responsibilities

• Develop and maintain scalable data pipelines and distributed data processing solutions using Spark, Scala/Java, and cloud platforms (AWS, GCP, or Azure)
• Build and enhance batch and real-time data processing solutions to support analytical and operational workloads
• Develop APIs and data services that enable secure/efficient access to enterprise data
• Create and maintain data models, ETL workflows, and processing frameworks that support business requirements
• Apply established data governance, security, and quality standards throughout the development lifecycle
• Collaborate with engineers, product teams, and business stakeholders to understand requirements and deliver reliable data solutions
• Troubleshoot production issues, optimize data processing performance, and improve system reliability
• Participate in code reviews, testing, and continuous improvement initiatives to maintain engineering quality.
• Continuously learn and adopt new technologies, tools, and engineering best practices

Benefits

• Comprehensive health benefits and programs (medical, vision, dental, life insurance)
• 401(k)
• Employee discount
• Short term disability
• Long term disability
• Paid sick leave
• Paid national holidays
• Paid vacation

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level