Senior Data Engineer

• Does this position require a security clearance? No
• Years 3 to 5+ years
• Additional Info Visa / work permit sponsorship is not available for this position
• Applicants are required to read, write, and speak the following languages English

As OCI’s development pipeline expands, reliable data infrastructure, strong data governance, and consistent reporting are essential to informed decision-making  Data Engineering and Analytics function connects technical data capabilities with business priorities—improving operational efficiency, strengthening cross-functional visibility, and enabling leadership to make data-backed investments and risk-aware decisions.

OCI is seeking a highly motivated individual with expertise in data engineering and analytics, strong communication skills, and a passion for solving complex business problems. Responsibilities include building and maintaining scalable data pipelines, integrating disparate data sources, and developing trusted datasets, dashboards, and actionable insights across OCI’s strategic initiatives. The ideal candidate combines hands-on technical expertise with business acumen to translate complex data into clear recommendations that advance OCI’s strategic and financial objectives.

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.

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.

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