Principal Data Engineer

The Principal Data Engineer role at Oracle, based onsite in Nashville, TN, leads Data Engineering, BI, and Analytics initiatives for OCI, combining hands-on data engineering with program leadership to design scalable data platforms and reporting solutions across Oracle Cloud Infrastructure.

RESPONSIBILITIES — DATA ENGINEERING & ANALYTICS LEADERSHIP

• Design, build, and scale data pipelines that aggregate information from multiple OCI systems and services.
• Develop robust data models, datasets, and reporting frameworks that provide actionable insights for engineering, operations, customer success, and executive leadership.
• Architect and implement scalable analytics platforms that support strategic customer programs and operational decision-making.
• Design and maintain enterprise-grade data solutions that improve visibility into customer adoption, operational health, service performance, and business outcomes.
• Build and automate data ingestion, transformation, and reporting processes to reduce manual effort and improve data accuracy.
• Establish data quality, governance, lineage, and observability standards across critical business datasets.
• Partner with engineering teams to define telemetry, instrumentation, and data collection strategies.
• Perform deep analysis of large and complex datasets to identify trends, opportunities, risks, and operational bottlenecks.
• Drive adoption of modern data engineering best practices, tools, and technologies across the organization.

RESPONSIBILITIES — BUSINESS INTELLIGENCE & EXECUTIVE REPORTING

• Design and deliver Business Intelligence solutions that provide actionable visibility into customer health, operational performance, and strategic business objectives.
• Develop executive dashboards, scorecards, KPI frameworks, and reporting solutions used by senior leadership for decision-making.
• Partner with business leaders to define success metrics, operational indicators, and reporting requirements.
• Build scalable semantic models and reporting datasets that enable self-service analytics across multiple organizations.
• Transform raw operational and engineering data into meaningful business insights and recommendations.
• Standardize reporting methodologies and establish trusted sources of truth for key organizational metrics.
• Support strategic planning, investment decisions, and customer engagement initiatives through data-driven analysis.

RESPONSIBILITIES — TECHNICAL PROGRAM MANAGEMENT & STRATEGIC EXECUTION

• Lead large, complex, cross-functional initiatives spanning engineering, product, operations, and executive leadership teams.
• Break down ambiguous business problems into actionable technical workstreams and measurable deliverables.
• Develop functional specifications and drive successful execution from concept through delivery.
• Identify process gaps and establish scalable mechanisms that improve organizational efficiency and execution.
• Manage program schedules, dependencies, risks, and stakeholder communications.
• Anticipate bottlenecks, proactively manage escalations, and balance technical constraints with business priorities.
• Drive alignment across OCI organizations toward shared objectives and customer outcomes.
• Lead interactions with cross-functional teams consisting of Engineers, Product Managers, Architects, Customer Success leaders, and Executive Leadership.
• Thrive in a fast-paced, highly ambiguous environment while maintaining focus on delivering measurable business value.

RESPONSIBILITIES — DATA PROCESSING & PIPELINING

• Mentors less experienced team members to identify data requirements and business objectives of a project or initiative.
• Provides expertise on the design and participates in building of data infrastructure to optimize data processing from a variety of data sources.
• Independently analyzes, designs, and troubleshoots data flows based on business needs.
• Participates in architecture, performance, and security reviews of the technical solution.
• Adjusts data collection processes that involve indexing and query optimizations for optimal performance.
• Builds ETL pipelines to support efficient and scalable data collection and extraction.
• Engages with and holds upstream and downstream teams accountable for predefined SLAs.
• Manages relationships with data providers.

RESPONSIBILITIES — DATA GOVERNANCE

• Independently designs and implements data governance policies and procedures for data handling to maintain consistency, integrity, accuracy, and reliability.
• Leads the redaction of PII and PHI data to ensure privacy and security compliance.
• Ensures minimal data collection and usage in accordance with data minimization principles.
• Implements data security measures to protect data from unauthorized access or disclosure and escalates issues as needed.
• Ensures data compliance with relevant laws, regulations, and industry standards.

RESPONSIBILITIES — DATA VALIDATION & QUALITY ASSURANCE

• Contributes to the design and implementation of rigorous data validation and integrity checks to mitigate quality issues.
• Mentors team members to define data annotation and labeling processes to ensure data quality.
• Identifies opportunities for automation of data validation and governance processes.
• Independently corrects deviations and non-conformance when identified.

RESPONSIBILITIES — DATA PIPELINE DESIGN

• Leverages advanced knowledge of ETL processes to design, develop, and optimize automated, scalable data pipeline architectures.
• Implements advanced data storage solutions to store processed data for analysis and access.
• Mentors less experienced team members to manage day-to-day data pipeline and storage operations.

RESPONSIBILITIES — DATA SOLUTIONS ENGINEERING

• Works independently and collaboratively in an agile environment to develop, maintain, and debug advanced data solutions that are scalable, efficient, cost-effective, and reliable.
• Reviews runnable code and supports testing and debugging with junior team members.
• Evaluates new technologies to enhance data solutions.
• Enforces and documents code standards and guidance within the team.
• Creates documentation for design decisions and gathers broader architectural feedback before implementing.
• Gathers data and evidence to secure necessary approvals.

CORE RESPONSIBILITIES — PLANNING & EXECUTION

• Manages and coordinates moderately complex tasks, ensuring timely completion and alignment with requirements for a moderately sized project.
• Delegates, monitors, and prioritizes work across multiple projects, providing technical oversight and adapting plans as resources or timelines shift.

CORE RESPONSIBILITIES — COLLABORATION & PARTNERSHIP

• Collaborates across the organization to align on expectations and achieve shared objectives.
• Understands business leaders, stakeholders, and customers to ensure solutions meet their needs.
• Fosters inclusivity by seeking diverse perspectives and ensuring others feel heard and respected.

CORE RESPONSIBILITIES — PROBLEM SOLVING

• Identifies and addresses moderately complex issues by analyzing data to determine solutions.
• Escalates unresolved or critical issues with a thorough assessment and suggests solutions.
• Documents problem solving strategies and contributes to improvements.

CORE RESPONSIBILITIES — CONTINUOUS LEARNING

• Pursues learning opportunities to expand knowledge and stay abreast of industry trends.
• Seeks feedback and training to improve skills.
• Coaches and mentors junior teammates, promoting knowledge sharing.

CORE RESPONSIBILITIES — CONTINUOUS IMPROVEMENT

• Develops ideas and collaborates on process improvements across teams, evaluating impact for stakeholders.
• Solicits feedback on alternative approaches for ongoing improvement.

CORE RESPONSIBILITIES — PERFORMANCE AND DEVELOPMENT

• Contributes to the talent development pipeline by participating in candidate interviews and providing hiring recommendations.

REQUIREMENTS

• BS degree or equivalent experience in Computer Science, Engineering, Information Systems, Data Science, or related field
• 7+ years of experience in Data Engineering, Analytics Engineering, Technical Program Management, Software Engineering, or related technical roles
• Strong experience designing, building, and maintaining large-scale data pipelines, ETL/ELT frameworks, and cloud-based data platforms
• Experience developing BI solutions, executive dashboards, KPI frameworks, and operational reporting systems
• Advanced SQL skills and experience working with large-scale datasets
• Experience with data modeling, data warehousing, analytics platforms, and reporting architectures
• Strong understanding of cloud technologies, distributed systems, and software development lifecycles
• Demonstrated ability to analyze complex datasets and translate findings into actionable business recommendations
• Experience partnering with engineering, product, operations, and business stakeholders to define requirements and deliver scalable data solutions
• Strong written and verbal communication skills across technical and executive audiences
• Proven ability to lead large, cross-functional initiatives and drive execution across organizational boundaries
• MS degree or equivalent experience in Computer Science, Data Engineering, Analytics, or related field
• 10+ years of experience in Data Engineering, Analytics Platforms, BI, Technical Program Management, or Software Development
• Experience building enterprise-scale data lakes, data warehouses, and analytics platforms
• Experience with cloud-native architectures, distributed systems, and OCI services
• Experience with Spark, Kafka, Airflow, Databricks, Snowflake, BigQuery, OCI Data Flow, or similar platforms
• Experience with Oracle Analytics Cloud (OAC), Tableau, Power BI, Looker, or comparable BI platforms
• Experience implementing data governance, data quality, metadata management, and observability frameworks
• Experience developing self-service analytics solutions and semantic data models
• Experience working directly with large enterprise customers and strategic cloud initiatives

TECHNOLOGIES

• Spark, Kafka, Airflow, Databricks, Snowflake, BigQuery, OCI Data Flow
• Oracle Analytics Cloud (OAC), Tableau, Power BI, Looker
• SQL, Oracle Cloud Infrastructure (OCI)

WHAT SUCCESS LOOKS LIKE

• Trusted data platforms and BI solutions become the foundation for decision-making across OCI Strategic Customer Engineering.
• Executive leaders have real-time visibility into customer outcomes, operational performance, and business health.
• Manual reporting processes are automated and replaced with scalable, self-service analytics capabilities.
• Strategic customer programs execute more effectively through improved data accessibility, insight generation, and operational transparency.
• Cross-functional teams align around a common set of metrics, objectives, and business outcomes.
• Data-driven insights directly influence customer success, operational excellence, and OCI growth initiatives.