Data Engineer - Target Tech and AI

Target • Minneapolis, MN

13d • Hybrid

About The Position

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.

Requirements

• 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.
• 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

Nice To Haves

• Google Cloud certifications preferred

Responsibilities

• 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

Benefits

• comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more
• 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: Mid Level
• Education Level: Associate degree