Principal Data Engineer, Epirus

• The ideal candidate will bring experience with SQL, Python, ETL (Extract, Transform, Load) processes, and cloud platforms, along with a strong focus on integrating enterprise systems, enabling seamless data flow across Palantir Foundry, Oracle ERP, MES, PDM, Jira and other business-critical systems
• 8+ years of experience as a data engineer
• Oracle Expertise: Proficient in Oracle Integration Cloud, Oracle Autonomous Database, and Oracle Analytics Cloud
• SQL Skills: Advanced knowledge of SQL, including window functions, stored procedures, and CTEs
• Python Proficiency: Hands-on experience with Python for ETL, data analysis, and API integration
• ETL Tools: Familiarity with Oracle Cloud Data Integration and other ETL frameworks
• System Integration: Experience integrating enterprise systems, including ERP and MES, with a focus on transaction reliability and scalability
• Cloud Technologies: Experience with Oracle Cloud Infrastructure (OCI) and related tools
• Visualization Tools: Experience creating dashboards and reports using Oracle Analytics Cloud, Tableau, or Power BI

Desirable

• We are seeking a skilled Principal Data Engineer to design, implement, and manage data integration and transformation processes using Cloud and associated technologies.
• This role presents a unique opportunity to work on cutting-edge Oracle Cloud and Palantir technologies while developing scalable ETL pipelines for large-scale data processing
• Cloud Integration & Data Pipeline Development
• Design and implement scalable data pipelines to extract, transform, and load data using Oracle Cloud Integration tools and Foundry
• Develop integrations between Foundry, Oracle ERP, MES, and other enterprise systems, focusing on transaction monitoring and data synchronization
• Leverage Oracle Integration Cloud (OIC) for process automation and real-time data flow
• Data Modeling & Warehousing
• Establish and maintain robust data lake and data warehouse structures for critical systems
• Define and enforce schemas and structured datasets for enterprise-wide access
• Utilize Cloud Data Integration tools to build and manage data models
• ETL Processes
• Develop and maintain ETL pipelines using Python and Cloud tools to ingest and process data from APIs and other sources
• Perform heavy data transformations and ensure data quality before loading into Cloud databases
• Orchestrate and schedule ETL workflows using Oracle Autonomous Database and other cloud-native tools
• System Integration & Best Practices
• Implement best practices for system integration, including error handling, transaction staging, logging, and retry logic
• Build scalable and resilient integrations between Oracle systems and external platforms using REST and SOAP APIs
• Data Analytics & Visualization
• Enable data-driven decision-making by providing access to clean and structured data through SQL and Business Intelligence tools
• Create dashboards and reports using Analytics Cloud, Tableau, or Power BI
• Cloud Technologies
• Leverage Oracle Cloud Infrastructure (OCI) for data storage, processing, and analytics
• Explore and integrate cloud-based solutions like Palantir Foundry, Oracle Data Flow, Oracle Data Catalog, and Oracle Big Data Service
• Use Oracle cloud-native tools to ensure efficient data management and accessibility
• Continuous Learning & Development
• Pursue Oracle certifications and stay updated on the latest Oracle Cloud tools and technologies
• Experiment with new tools and frameworks, such as dbt or Apache Spark, to enhance integration capabilities