:MS or BS in Computer Science or Equivalent6-10+ years of relevant experienceKey Responsibilities:Feature Engineering Pipelines
Design and implement data pipelines for feature extraction, transformation, and enrichment at scale using tools like Apache Spark, Airflow, or Prefect.
Collaborate with data scientists to automate and optimize feature engineering workflows.
Develop real-time and batch processing pipelines to support machine learning and analytics workloads.
Ensure pipelines are resilient, maintainable, and scalable to handle large volumes of structured and unstructured data.
Secure Data Storage & Management
Architect and manage secure storage solutions leveraging relational (SQL) and non-relational (NoSQL) databases like Oracle, DynamoDB, and MongoDB.
Implement encryption techniques, data masking, and role-based access controls (RBAC) to safeguard sensitive data.
Establish data retention policies and backup strategies to ensure compliance with data privacy regulations.
Track data lineage and manage metadata using tools like Apache Atlas or DataHub.
Data Infrastructure & Tools
Build and manage scalable ETL/ELT pipelines to streamline data ingestion and transformation processes.
Leverage cloud-based services (AWS, GCP, Azure) for secure storage and data processing.
Integrate distributed systems like Hadoop and Kafka for high-volume data handling.
Collaboration & Leadership
Partner with data science and analytics teams to understand feature engineering needs and translate them into technical solutions.
Lead efforts to enhance the security and reliability of data pipelines and storage systems.
Mentor junior engineers on best practices in data engineering and secure software design.
Qualifications:
Strong background in data structures, algorithms, and system design.
Hands-on experience with feature engineering pipelines, ETL/ELT tools, and secure data storage solutions.
Proficiency in programming languages like Python, Java, or Scala.
In-depth knowledge of data privacy regulations and compliance requirements.
Familiarity with distributed systems, real-time data processing, and cloud platforms.
This role offers the chance to work on cutting-edge data engineering challenges, ensuring secure and efficient handling of large-scale data. If you are passionate about building feature-rich and secure platforms, we encourage you to apply.Career Level - IC4Responsibilities:Key Responsibilities:Feature Engineering Pipelines
Design and implement data pipelines for feature extraction, transformation, and enrichment at scale using tools like Apache Spark, Airflow, or Prefect.
Collaborate with data scientists to automate and optimize feature engineering workflows.
Develop real-time and batch processing pipelines to support machine learning and analytics workloads.
Ensure pipelines are resilient, maintainable, and scalable to handle large volumes of structured and unstructured data.
Secure Data Storage & Management
Architect and manage secure storage solutions leveraging relational (SQL) and non-relational (NoSQL) databases like Oracle, DynamoDB, and MongoDB.
Implement encryption techniques, data masking, and role-based access controls (RBAC) to safeguard sensitive data.
Establish data retention policies and backup strategies to ensure compliance with data privacy regulations.
Track data lineage and manage metadata using tools like Apache Atlas or DataHub.
Data Infrastructure & Tools
Build and manage scalable ETL/ELT pipelines to streamline data ingestion and transformation processes.
Leverage cloud-based services (AWS, GCP, Azure) for secure storage and data processing.
Integrate distributed systems like Hadoop and Kafka for high-volume data handling.
Collaboration & Leadership
Partner with data science and analytics teams to understand feature engineering needs and translate them into technical solutions.
Lead efforts to enhance the security and reliability of data pipelines and storage systems.
Mentor junior engineers on best practices in data engineering and secure software design.
Qualifications:
Strong background in data structures, algorithms, and system design.
Hands-on experience with feature engineering pipelines, ETL/ELT tools, and secure data storage solutions.
Proficiency in programming languages like Python, Java, or Scala.
In-depth knowledge of data privacy regulations and compliance requirements.
Familiarity with distributed systems, real-time data processing, and cloud platforms.
This role offers the chance to work on cutting-edge data engineering challenges, ensuring secure and efficient handling of large-scale data. If you are passionate about building feature-rich and secure platforms, we encourage you to apply.About Us:As a world leader in cloud solutions, Oracle uses tomorrow's technology to tackle today's challenges. We've partnered with industry-leaders in almost every sector-and continue to thrive after 40+ years of change by operating with integrity.We know that true innovation starts when everyone is empowered to contribute. That's why we're committed to growing an inclusive workforce that promotes opportunities for all.Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs.We're committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing or by calling +1 888 404 2494 in the United States.Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.