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Oracle cloud engineer

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Job Description - Oracle cloud engineer

  • Digital Transformation Project
  • Young and international culture
  • AI initiative
Role Summary We are seeking an experienced Engineer to play a key role in the migration of our on-premise / legacy data warehouse to Oracle Cloud Infrastructure (OCI). This role will also contribute to AI-oriented initiatives, enabling advanced analytics, machine learning, and data-driven decision-making across the organization.
The ideal candidate combines strong data engineering fundamentals with cloud migration experience and a modern mindset toward AI, automation, and scalable analytics architectures.
Key Responsibilities

Data Warehouse Migration & Modernization
  • Lead and execute the migration of enterprise data warehouse solutions to Oracle Cloud (OCI), ensuring data integrity, performance, and security
  • Design and implement cloud-native data architectures using Oracle Autonomous Data Warehouse (ADW), Object Storage, and related OCI services
  • Refactor and optimize existing ETL/ELT pipelines for cloud scalability and cost efficiency
  • Migrate and modernize legacy SQL, PL/SQL, and BI workloads for cloud-based analytics
  • Collaborate with architecture, infrastructure, and security teams to align with cloud standards and governance


Data Engineering & Platform Development
  • Design and develop reliable, scalable data pipelines for structured and semi-structured data
  • Implement data quality checks, lineage, and monitoring to ensure trusted datasets
  • Support near real-time and batch processing use cases as required
  • Optimize query performance, data models, and storage strategies in Oracle Cloud
  • Develop reusable data frameworks and automation scripts for repeatable deployments


AI & Advanced Analytics Enablement
  • Enable AI/ML use cases by preparing high-quality, analytics-ready datasets
  • Partner with data scientists and analytics teams to operationalize machine learning models
  • Support feature engineering, data versioning, and model training pipelines
  • Integrate AI-driven insights into downstream analytics, dashboards, or applications
  • Leverage Oracle Cloud AI/ML services or open-source ML frameworks where appropriate


Collaboration & Delivery
  • Work closely with business stakeholders, BI teams, and data science teams to translate requirements into data solutions
  • Contribute to agile delivery cycles, including sprint planning, estimations, and code reviews
  • Document architecture, data flows, and operational procedures
  • Mentor junior engineers and promote data engineering best practices
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
  • 5+ years of experience in data engineering, data warehousing, or analytics engineering
  • Hands-on experience with Oracle databases (e.g., Oracle DW, PL/SQL, SQL performance tuning)
  • Proven experience migrating data platforms to Oracle Cloud Infrastructure (OCI) or similar cloud environments
  • Strong expertise in ETL/ELT design, data modeling (dimensional, data vault, or similar), and SQL
  • Experience building and maintaining production-grade data pipelines
  • Solid understanding of cloud security, networking, and data governance concepts
AI & Modern Analytics Experience (Required / Strongly Preferred)
  • Experience supporting AI/ML or advanced analytics initiatives
  • Familiarity with machine learning data preparation, feature engineering, and model deployment workflows
  • Exposure to Python, Spark, or similar data processing frameworks
  • Understanding of MLOps or data platforms that support AI lifecycle management
Nice to Have
  • Experience with Oracle Autonomous Database, OCI Data Integration, OCI Data Science, or OCI AI services
  • Knowledge of open-source tools (e.g., Airflow, dbt, Spark)
  • Experience with BI tools and analytics platforms (e.g., Oracle Analytics, Power BI, Tableau)
  • Cloud certifications (Oracle Cloud, AWS, Azure, or GCP)
  • Experience working in large-scale transformation or modernization programs
What Success Looks Like
  • Successful migration of legacy data warehouse workloads to OCI with minimal disruption
  • Improved performance, scalability, and reliability of data platforms
  • High-quality, AI-ready datasets enabling advanced analytics and machine learning use cases
  • Strong collaboration across engineering, analytics, and business teams
  • Adoption of modern data engineering and cloud best practices


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