Job description

Designs and builds proper data pipelines required for optimal data collection and processing from a variety of data sources. Implements data governance policies and procedures for data handling to manage data consistency, integrity, accuracy, security, and reliability. Implements rigorous data validation and integrity checks to support data pipeline and model performance. Designs, develops, and optimizes automated and scalable data pipeline architectures using Extract, Transform, and Load (ETL) processes to build reusable data products, independently. Collaborates in an agile development environment to develop, maintain, and debug data solutions that are scalable, efficient, and reliable. Key Responsibilities Data Processing & Pipelining – Data Requirements, Collection, and Infrastructure: • Identifies data requirements and business objectives of a project or initiative in collaboration with cross-functional teams. • Designs and builds proper data pipelines required for optimal data processing from a variety of data sources. • Independently analyzes, designs, and troubleshoots data flows based on business needs. • Analyzes business requirements and translates that into a technical specification. • Adjusts data collection processes that involve indexing and query optimizations, for optimal performance. • Builds Extract, Transform, and Load (ETL) pipelines to support efficient data collection and extraction, independently. • Analyzes data sources for profiling the data to ensure pipeline build success. • Defines success and failure thresholds for data collection pipelines. Data Processing & Pipelining – Data Governance: • Implements data governance policies and procedures for data handling (e.g., data retention) to manage data consistency, integrity, accuracy, and reliability throughout the data lifecycle. • Redacts Personally Identifiable Information (PII) and Protected Health Information (PHI) data to ensure compliance with data privacy and security standards. • Follows data security measures to protect data from unauthorized access, use, disclosure, alteration, or destruction. • Ensures data compliance with relevant laws, regulation, and industry standards. Data Processing & Pipelining – Data Validation & Quality Assurance: • Implements rigorous data validation and integrity checks, identifying and addressing any data quality issues that could impact data pipeline and model performance. • Defines data annotation and labeling processes to ensure data quality, independently. • Designs and implements automation of data validation and governance. Data Pipeline and Solutions Engineering – Pipeline Design: • Independently designs, develops, and optimizes automated and scalable data pipeline architectures using ETL processes to build reusable data products. • Implements appropriate data storage solutions to store the processed data to be used in a scalable and optimized way for access and analysis. • Manages the flow of data pipeline and storage day-to-day operations. Data Pipeline and Solutions Engineering – Data Solutions Engineering: • Works independently and collaboratively in an agile development environment with other engineers to develop, maintain, and debug data solutions that are scalable, efficient, cost effective, and reliable. • Writes runnable code and performs testing and debugging of data solutions, independently. Core Responsibilities Planning & Execution: • Independently manages work, monitoring timelines and deliverables to ensure projects or initiatives stay on track and meet requirements. • Proactively prioritizes work and adapts to resource or timeline shifts, suggesting adjustments to maintain project efficiency. Collaboration & Partnership: • Collaborates across teams to align on expectations and achieve shared objectives. • Builds and maintains a comprehensive understanding of business, stakeholder, and/or customer needs to build and support effective partnerships. • Actively listens to diverse perspectives and asks questions to ensure understanding of others. Problem Solving: • Independently identifies and addresses standard and non-standard issues in accordance with standard practices, escalating more complex issues as appropriate. • Analyzes data and/or information from multiple sources to troubleshoot standard and non-standard errors. • Contributes to knowledge sharing and best practices. Continuous Learning: • Embraces continuous learning by actively seeking to build knowledge and new skills and/or tools and staying current with industry trends and best practices. • Seeks out and leverages feedback and training to improve skills. • Contributes to a culture of continuous learning and knowledge sharing with team members. Continuous Improvement: • Develops ideas and recommends updates to increase the efficiency and effectiveness of processes, protocols, and workflows within a team. • Seeks input from team members on alternative approaches and methods for improving work. Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $102,300 to $209,500 per annum. May be eligible for bonus and equity. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation. 9. 11 paid holidays 10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours. 11. Paid parental leave 12. Adoption assistance 13. Employee Stock Purchase Plan 14. Financial planning and group legal 15. Voluntary benefits including auto, homeowner and pet insurance The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment. This position is part of Oracle’s Life Sciences Services organization, which provides managed IT services to healthcare organizations that outsource their information technology operations to Oracle. The role will be based onsite at Southwest General Hospital in Middleburg Heights, Ohio. Candidates must reside in the greater Cleveland area and be available to work onsite as required to support the hospital’s operational and technology needs. ***Must have Fusion experience ***Must be local to Cleveland, Ohio or willing to relocate at own expense

Requirements

Must-haves

Data Processing & Pipelining – Data Requirements, Collection, and Infrastructure:
Identifies data requirements and business objectives of a project or initiative in collaboration with cross-functional teams.
Designs and builds proper data pipelines required for optimal data processing from a variety of data sources.
Independently analyzes, designs, and troubleshoots data flows based on business needs.
Analyzes business requirements and translates that into a technical specification.
Adjusts data collection processes that involve indexing and query optimizations, for optimal performance.
Builds Extract, Transform, and Load (ETL) pipelines to support efficient data collection and extraction, independently.
Analyzes data sources for profiling the data to ensure pipeline build success.
Defines success and failure thresholds for data collection pipelines.
Implements data governance policies and procedures for data handling (e.g., data retention) to manage data consistency, integrity, accuracy, and reliability throughout the data lifecycle.
Redacts Personally Identifiable Information (PII) and Protected Health Information (PHI) data to ensure compliance with data privacy and security standards.
Follows data security measures to protect data from unauthorized access, use, disclosure, alteration, or destruction.
Ensures data compliance with relevant laws, regulation, and industry standards.
Data Processing & Pipelining – Data Validation & Quality Assurance:
Implements rigorous data validation and integrity checks, identifying and addressing any data quality issues that could impact data pipeline and model performance.
Defines data annotation and labeling processes to ensure data quality, independently.
Designs and implements automation of data validation and governance.
Data Pipeline and Solutions Engineering – Pipeline Design:
Independently designs, develops, and optimizes automated and scalable data pipeline architectures using ETL processes to build reusable data products.
Implements appropriate data storage solutions to store the processed data to be used in a scalable and optimized way for access and analysis.
Manages the flow of data pipeline and storage day-to-day operations.
Data Pipeline and Solutions Engineering – Data Solutions Engineering:
Works independently and collaboratively in an agile development environment with other engineers to develop, maintain, and debug data solutions that are scalable, efficient, cost effective, and reliable.
Writes runnable code and performs testing and debugging of data solutions, independently.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

agile

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave