Data Engineer - Target Tech and AI

Job Id: R0000441374

The pay range is $75,400.00 - $135,700.00

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 TECH AS A DATA ENGINEER

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.

As a Data Engineer you will be responsible for building and optimizing data pipelines, integrating data from multiple sources and creating reliable, high-quality datasets that power analytics, reporting, machine learning and operational processes. You will join a collaboration and growing Data and Analytics team where you’re accountable for developing code and configuring software that generates required data in support of reporting and analysis for our global teams.

As a Data Engineer, you will:

• Design, develop, and maintain scalable data pipelines and data integration solutions to support business intelligence, analytics, and data science initiatives
• Translate business requirements into technical solutions by partnering with stakeholders, analysts, data scientists, and application teams
• Build and optimize ETL/ELT processes to ingest, transform, and deliver data from various internal and external sources
• Develop and maintain data models, curated datasets, and data products that support reporting, analytics, and operational use cases
• Design and implement cloud-native data solutions on Google Cloud Platform (GCP)
• Develop and optimize data processing workflows using modern big data technologies
• Ensure data quality, integrity, consistency, security, and governance across data platforms
• Support both batch and real-time data processing patterns using modern integration and streaming technologies
• Develop automated testing, monitoring, and alerting capabilities to ensure data pipeline reliability and performance
• Leverage AI-assisted development tools to improve productivity, code quality, documentation, testing, and troubleshooting
• Contribute to engineering best practices including code reviews, CI/CD automation, infrastructure as code, and DevOps principles
• Collaborate with cross-functional teams to troubleshoot issues and continuously improve data solutions
• Leverage AI-assisted development tools to improve productivity, code quality, documentation, testing, and troubleshooting.
• Contribute to engineering best practices including code reviews, CI/CD automation, infrastructure as code, and DevOps principles.
• Collaborate with cross-functional teams to troubleshoot issues and continuously improve data solutions

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

About you:

• 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent industry experience
• 1+ year of experience in Data Engineering, Software Engineering, BI Engineering or a related engineering skillset
• Strong programming skills in Python, Java, Scala, or a similar language
• Strong SQL development and query optimization skills
• Experience building and supporting ETL/ELT pipelines and data integration workflows
• Experience with modern data lake and data warehouse architectures
• Experience with Hadoop ecosystem technologies including Hive, HDFS and Spark
• Experience with streaming technologies such as Kafka or Pub/Sub
• Experience with workflow orchestration tools such as Airflow or Cloud Composer
• Knowledge of containerization technologies such as Docker and Kubernetes
• Familiarity with infrastructure-as-code tools such as Terraform
• Experience implementing data quality, metadata management and data governance
• Hands-on experience with Google Cloud Platform (GCP) data and analytics services such as BigQuery, Cloud Storage, Dataproc, Dataflow, Pub/Sub, Composer or similar technologies. Google Cloud certifications preferred
• Experience working with distributed data processing frameworks such as Apache Spark
• Familiarity with AI-powered development tools (e.g., GitHub Copilot, Gemini, ChatGPT, Cursor, or similar) and the ability to effectively leverage them to improve engineering productivity and solution quality
• Strong analytical, problem-solving and communication skills

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.

Benefits Eligibility

Americans with Disabilities Act (ADA)

In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.