Data Engineer - New Grad

Job Description

As a Junior Data Engineer, you will help build and maintain data pipelines and curated datasets that support analytics, reporting, and data science at Oracle. You’ll work with experienced data engineers, data scientists, and business partners to deliver reliable, well-documented datasets with clear expectations for quality, monitoring, and operational readiness.

Growth & Mentorship (What you can expect)

• Mentorship from experienced data engineers through pairing, code reviews, and a structured onboarding plan
• A clear learning plan and regular feedback to support your growth
• Opportunities to rotate across pipeline development, data modeling, data quality, and operational support as you ramp
• Support in building strong fundamentals in version control, testing, debugging, and performance basics

Key Responsibilities

Data Requirements, Collection, and Infrastructure

• Learn to identify data requirements and project goals
• Partner with analysts, data scientists, and engineering teams to translate requirements into implemented datasets and pipeline changes
• Build and troubleshoot batch and/or streaming pipelines to ingest, transform, and deliver data for analytics and reporting
• Help improve performance through query tuning and upstream data collection improvements (e.g., indexing and query optimizations)
• Write and maintain ETL/ELT workflows and reusable transformations using SQL and Python and/or Java
• Contribute to monitoring and alerting for pipeline health, failures, and data freshness

Data Governance & Security

• Assist with data governance practices across the data lifecycle (e.g., retention and classification) to support consistency, integrity, accuracy, and reliability
• Follow security controls to prevent unauthorized access, use, disclosure, alteration, or destruction of data

Data Validation & Quality Assurance

• Help implement data validation and integrity checks (e.g., reconciliation and anomaly checks) and troubleshoot data quality issues
• Contribute to data quality signals such as tests, documentation, and dataset metrics

Pipeline Design, Operations, and Delivery

• With mentorship, design and improve automated pipeline components that can be reused across use cases
• Assist with selecting and implementing storage approaches that support efficient access and analysis
• Support day-to-day pipeline operations (investigating failures, reruns, and follow-ups) and help improve reliability over time
• Work in an agile environment to develop, test, debug, and document data solutions
• Participate in code reviews and release processes; follow secure coding and data handling practices

Core Responsibilities

• Planning & Execution: Track timelines and deliver work aligned to requirements; adjust priorities as needs change
• Collaboration: Communicate clearly with technical and non-technical stakeholders; ask questions and incorporate feedback
• Problem Solving: Troubleshoot issues using information from multiple sources; escalate when appropriate
• Continuous Learning: Build skills through training, feedback, and continuous improvement of tools and processes