Sr Data Engineer - Finance Technology Platform (PySpark, Hadoop, Cloud)

Target • Brooklyn Park, MN

2d • $98,000 - $176,000 • Hybrid

About The Position

Finance Technology within Core Retail Services powers the financial backbone of Target's enterprise operations. We build and support platforms that enable critical business capabilities across Accounts Payable, Accounts Receivable, Vendor Income, Treasury, Financial Planning, Core Accounting, Revenue & Receivables, and Enterprise Financial Controls. Our financial reporting platform brings these data domains together to deliver near real-time insights, enabling accurate financial reporting and faster, data-driven decision-making. Join our global in-house technology team of more than 5,000 engineers, data scientists, architects, and product managers who are striving to make Target the most convenient, safe, and joyful place to shop. We use agile practices and leverage open-source technologies to build best-in-class solutions for our team members and guests, with a strong focus on diversity and inclusion, experimentation, and continuous learning.

As a Senior Data Engineer, you will design, develop, and optimize scalable, high-performance data solutions that power critical financial systems across Target. You will contribute to the evolution of our data architecture, ensuring it meets both functional and non-functional business requirements while delivering reliability, efficiency, and scalability. Leveraging your expertise in big data technologies, distributed systems, and cloud platforms, you will build and optimize data pipelines, analytics solutions, and real-time data services. Working closely with engineers, product managers, and business stakeholders, you'll help deliver enterprise-scale data capabilities that support financial reporting and operational decision-making.

Requirements

• 4-year degree in Quantitative disciplines (Science, Tech, Engineering, Mathematics) or equivalent industry experience required
• 5 plus years of experience in data engineering, software development or distributed systems
• Demonstrated expertise in big data technologies such as Hadoop, Spark, and distributed processing frameworks
• Strong programming skills in PySpark, Scala, and/or Java
• Experience with cloud platforms (AWS, GCP, or Azure) and associated data services (e.g. S3, BigQuery, Databricks, EMR, Snowflake)
• Experience developing APIs using REST, GraphQL, or gRPC to support real-time and batch data access
• Experience with streaming and real-time data technologies such as Kafka, Flink, or Kinesis
• Strong understanding of data modeling, ETL pipeline design, and performance optimization
• Familiarity with data governance, security, and compliance in enterprise-scale data environments
• Strong analytical and problem-solving skills with the ability to work effectively in complex environments
• Excellent communication and collaboration skills, with experience partnering across engineering, product, and business teams
• Self-driven and results-oriented, with strong ownership, sound judgment and the ability to move quickly while maintaining high technical standards
• Collaborative team player with a commitment to continuous learning, knowledge sharing, and building reliable tech systems that create business value

Nice To Haves

• MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics or a related technical field preferred

Responsibilities

• Design, build, and maintain scalable, high-performance data pipelines and distributed data processing solutions using Spark, Scala/Java, and cloud platforms (AWS, GCP, or Azure)
• Develop and optimize batch and real-time data processing solutions to ensure reliable, high-quality data for analytical and operational use
• Build APIs and data services that provide low-latency, high-throughput access to data for downstream applications
• Design and optimize data models, ETL workflows, and processing frameworks to improve performance, scalability, and cost efficiency
• Apply data governance, security, and compliance best practices throughout the data lifecycle
• Collaborate with data scientists, product teams, and business stakeholders to understand requirements and deliver scalable data solutions
• Contribute to the design, implementation, and continuous improvement of enterprise data platforms and services
• Evaluate emerging technologies and help drive adoption of engineering best practices in big data, cloud computing, and API development
• Mentor junior engineers through code reviews, technical guidance, and knowledge sharing while fostering a collaborative engineering culture.

Benefits

• Comprehensive health benefits and programs, which may include 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: Senior
• Education Level: Associate degree