Oracle
Software Developer 4
Job Description
MS or BS in Computer Science or Equivalent
6-10+ years of relevant experience
Strong Software Engineering Fundamentals & API Development
- Proficiency in Data Structures & Algorithms: Critical for designing efficient systems that handle large-scale data.
- System Design: Ability to design scalable, fault-tolerant systems and services.
- Coding Skills: Expertise in languages like Java, Python, or Scala, especially for backend systems development.
- RESTful Services: Proven experience in designing and building robust APIs for data access and integration.
- GraphQL: Knowledge of modern data access technologies for flexible querying.
- Microservices Architecture: Experience with creating microservices that handle different aspects of data management.
Data Architecture and Design Patterns
- Database Design: Strong knowledge of both relational (SQL) and non-relational (NoSQL) databases like Oracle, MongoDB, Cassandra, or DynamoDB.
- Data Modeling: Ability to design and manage data models for efficient storage and retrieval.
- Data Warehousing: Experience with data warehouses and ETL processes.
- Data Access Controls: Experience with role-based access control (RBAC) and encryption techniques to secure sensitive data.
- Metadata Management: Familiarity with tools and processes for tracking data lineage, metadata catalogs (e.g., Apache Atlas, DataHub).
- Ability to handle complex data-related challenges, from dealing with incomplete or inconsistent data to optimizing performance.
- Strong analytical thinking to derive insights from data and build solutions that improve platform performance.
Data Pipeline and Orchestration
- ETL/ELT Tools: Experience with data pipeline orchestration tools like Airflow, Prefect, or Dagster.
- Automation & CI/CD: Familiarity with setting up CI/CD pipelines for data infrastructure.
- Distributed Systems: Experience with technologies like Hadoop, Spark, Kafka, and Flink for managing large-scale data processing pipelines.
- Data Streaming: Familiarity with real-time data processing frameworks (e.g., Apache Kafka, Pulsar, or RabbitMQ).
- Cloud Platforms: Hands-on experience with cloud-based data services (AWS, GCP, Azure), including data storage (S3, GCS) and data analytics (EMR, Dataproc).
Leadership and Collaboration
- Team Leadership: Ability to mentor junior engineers and guide them in building robust, scalable systems.
- Cross-Functional Collaboration: Experience working closely with data scientists, analysts, and other engineers to deliver on the platform’s objectives.
- Stakeholder Management: Strong communication skills for presenting technical decisions to non-technical stakeholders.
Career Level - IC4
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