Sr Data Engineer - Finance Technology Platform (PySpark, Hadoop, Cloud)
Target
- Location
- 7000 Target Pkwy N,NCD-0375 Brooklyn Park,MN 55445
- Work model
- On-Site
- Level
- Senior
- Salary
- $98k – $176k/yr
- Posted
- 6h ago
Skills
About this role
The pay range is $98,000.00 - $176,000.00 Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits . JOIN TARGET AS A SR DATA ENGINEER – FINANCE AI PLATFORM About Us: Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here .
Team
Overview: 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.
Position
Overview: 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.
Key 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