Data Engineer, Finance AI (PySpark)
Target
Brooklyn Park, MN1–6 yrs15h agovia LinkedIn
This job at a glance
- Who can apply
- 1–6 years of experience
- Must know
- AgileETLProduct managementJavaScalaAWS
- Work
- On-site in Brooklyn Park
- Pay
- Not stated by the employer.
- Skill demand
- ETL61%Agile16%Product management14%Java10%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 7, 2026 · still open
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About the Role
As a Data Engineer, you will develop and maintain scalable data solutions that support Target's financial systems and enterprise reporting capabilities. Working as part of an agile engineering team, you'll build reliable data pipelines, develop data services, and help deliver high-quality data that enables business insights and operational excellence. You'll collaborate closely with engineers, product managers, data scientists, and business partners to build efficient, scalable, and maintainable data solutions while continuing to grow your technical expertise in cloud technologies and distributed data processing.
Key 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
Requirements & Tech Stack
- 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 (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
Qualifications
- 4 year degree in Computer Science, Applied Mathematics, Physics, Information Technology, Engineering, etc. or equivalent industry experience