Data Engineer

Role Overview

We are collaborating with Target to hire a Data Engineer. In this pivotal role, you will architect and optimize robust data pipelines, seamlessly integrate diverse data sources, and construct reliable datasets that empower analytics and reporting for our global teams.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and integration solutions to support business intelligence, advanced analytics, and data science initiatives.
• Translate complex business requirements into technical strategies by partnering with stakeholders, analysts, scientists, and application development teams.
• Build and optimize ETL/ELT processes to ingest, transform, and deliver high-quality data from various internal and external sources.
• Develop and maintain sophisticated data models, curated datasets, and data products that drive reporting, analytics, and operational use cases.
• Design and implement cloud-native solutions leveraging Google Cloud Platform (GCP) services including BigQuery, Dataflow, Dataproc, Pub/Sub, Composer, and Cloud Storage.
• Develop and optimize processing workflows using modern big data technologies like Apache Spark within the Hadoop ecosystem.
• Ensure rigorous standards for data quality, integrity, consistency, security, and governance across all platforms.
• Support both batch and real-time data processing patterns utilizing state-of-the-art streaming technologies such as Kafka or Pub/Sub.
• Create automated testing, monitoring, and alerting capabilities to guarantee pipeline reliability and peak performance.
• Leverage AI-assisted development tools (e.g., GitHub Copilot, Gemini) to enhance productivity, code quality, documentation, testing, and troubleshooting.
• Contribute to engineering best practices including peer code reviews, CI/CD automation, Infrastructure as Code (IaC), and DevOps principles using Docker, Kubernetes, and Terraform.