Data Engineer - Finance AI (PySpark)
About The Position
As a Data Engineer in Target’s Finance AI Solutions team, you will develop and maintain scalable data solutions supporting Target’s financial systems and enterprise reporting capabilities. Working as part of an agile engineering team, you will build reliable data pipelines, develop data services, and help deliver high-quality data for business insights and operational excellence. You will collaborate with engineers, product managers, data scientists, and business partners to build efficient, scalable, and maintainable solutions while growing your technical expertise in cloud technologies and distributed data processing. Finance Technology within Core Retail Services powers financial capabilities across Accounts Payable, Accounts Receivable, Vendor Income, Treasury, Financial Planning, Core Accounting, Revenue & Receivables, and Enterprise Financial Controls. Its financial reporting platform brings these data domains together to provide near-real-time insights for accurate reporting and data-driven decisions. Target’s global in-house technology team uses agile practices and open-source technologies.
Requirements
- Four-year degree in Computer Science, Applied Mathematics, Physics, Information Technology, Engineering, or a related field, or equivalent industry experience.
- At least 1 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 such as 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 such as AWS, GCP, or Azure.
- Build and enhance batch and real-time data-processing solutions for analytical and operational workloads.
- Develop APIs and data services that enable secure and 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
- Eligible team members and their dependents may receive comprehensive health benefits, which may include medical, vision, dental, and life insurance.
- 401(k)
- Employee discount
- Short-term disability
- Long-term disability
- Paid sick leave
- Paid national holidays
- Paid vacation
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
