Senior Engineer - Fraud & Abuse Data Engineering

The pay range is $95,000.00 - $

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

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.

As a Senior Engineer, you serve as a specialist in the engineering team that supports the product. You help develop and gain insight in the application architecture. You can distill an abstract architecture into concrete design and influence the implementation. You show expertise in applying the appropriate software engineering patterns to build robust and scalable systems. You are an expert in programming and apply your skills in developing the product.

You have the skills to design and implement the architecture on your own, but choose to influence your fellow engineers by proposing software designs, providing feedback on software designs and/or implementation. You show good problem solving skills and can help the team in triaging operational issues. You leverage your expertise in eliminating repeat occurrences. Use your skills, experience and talents to be a part of groundbreaking thinking and visionary goals.

As a Senior Engineer, you’ll take the lead as you…

• Design, build, and operate scalable batch and streaming data pipelines (Kafka) and ETL/ELT workflows across Hadoop and Google Cloud Platform (GCP); implement monitoring/alerting to meet reliability and SLA targets.
• Develop high-performance distributed processing with Python, Spark, and Hive; optimize jobs, storage, and throughput for large-scale, high-volume datasets and cost efficiency.
• Deliver curated, trustworthy datasets for analytics, reporting, and ML with strong data quality, lineage, and governance.
• Partner with data scientists to operationalize ML on GCP (e.g., Vertex AI), building MLOps pipelines for training, deployment, CI/CD, monitoring, and automated retraining.
• Integrate on‑prem Hadoop data lakes with GCP services to enable seamless hybrid data and model workflows.
• Collaborate with analysts and product engineers to ensure data is accessible, high-quality, and actionable; provide technical mentorship to junior engineers.
• Uphold security, privacy, and regulatory compliance across all data engineering practices.
• Continuously evaluate technologies and design patterns, and drive improvements in performance, scalability, and cost across Hadoop and GCP environments.

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

• BA/BS or equivalent; 4+ years building large-scale data systems.
• Proficient in core platforms; writes organized, maintainable code across multiple languages and distributed frameworks.
• Skilled in package configuration/deployment and building custom solutions.
• Designs robust tests; troubleshoots and resolves routine and non‑routine issues independently.
• Delivers high-performance, scalable, secure solutions (high throughput/low latency).
• Operates effectively in Agile: communicates clearly with partners, aligns team priorities, and understands guest/business impact.
• Influences and applies data/engineering standards and policies; maintains expertise and stays current through ongoing learning.

• Strong proficiency in Python and SQL.
• Hands‑on experience with Apache Spark and the Hadoop ecosystem (HDFS, Hive, Pig, Oozie, Sqoop,…