Principal Data Engineer

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

Responsibilities

• Design, build, and scale data pipelines that consolidate data from multiple OCI systems and services.
• Create robust data models, datasets, and reporting frameworks supporting engineering, operations, customer success, and executive leadership.
• Architect scalable analytics platforms that undergird strategic customer programs and operational decisions.
• Develop enterprise-grade data solutions to improve visibility into customer adoption, health, service performance, and business outcomes.
• Automate data ingestion, transformation, and reporting processes to reduce manual effort and increase data accuracy.
• Establish standards for data quality, governance, lineage, and observability across critical datasets.
• Collaborate with engineering teams to define telemetry, instrumentation, and data collection strategies.
• Perform in-depth analyses of large, complex datasets to surface trends, opportunities, risks, and bottlenecks.
• Promote modern data engineering practices, tools, and technologies across the organization.
• Lead large, cross-functional initiatives spanning engineering, product, operations, and executive leadership.
• Decompose ambiguous business problems into actionable technical workstreams and measurable deliverables.
• Develop functional specifications and drive execution from concept through delivery.
• Identify process gaps and implement scalable mechanisms to improve efficiency and execution.
• Manage program schedules, dependencies, risks, and stakeholder communications.
• Anticipate bottlenecks, escalate when needed, and balance technical constraints with business priorities.
• Align OCI organizations toward shared objectives and customer outcomes.
• Engage with cross-functional teams including Engineers, Product Managers, Architects, Customer Success leaders, and Executive Leadership.
• Operate effectively in a fast-paced, ambiguous environment while delivering measurable business value.

Data Engineering & Analytics Leadership

• Mentor junior team members to capture data requirements and business objectives for initiatives.
• Contribute expertise to the design and construction of data infrastructure that optimizes processing from diverse sources.
• Analyze, design, and troubleshoot data flows, participating in architecture reviews for performance and security.
• Adapt data collection processes and ETL pipelines for better efficiency and accuracy.
• Engage with upstream and downstream teams to ensure adherence to defined SLAs.
• Manage relationships with data providers to sustain reliable data access.

Business Intelligence & Executive Reporting

• Deliver BI solutions that provide clear visibility into customer health, operations, and strategic objectives.
• Develop executive dashboards, KPI frameworks, scorecards, and reporting used by senior leadership.
• Partner with business leaders to define success metrics and reporting requirements.
• Build scalable semantic models and datasets enabling self-service analytics across units.
• Transform raw data into actionable insights and recommendations for decision makers.
• Standardize reporting methodologies and establish trusted sources of truth for key metrics.
• Support strategic planning, investments, and customer engagement through data-driven analysis.

Technical Program Management & Strategic Execution

• Lead large, cross-functional programs spanning engineering, product, operations, and leadership.
• Break down complex problems into executable technical workstreams with clear deliverables.
• Draft functional specifications and drive end-to-end delivery from concept to rollout.
• Identify process gaps and implement scalable mechanisms to improve organizational efficiency.
• Oversee program schedules, dependencies, risks, and stakeholder communications.
• Manage bottlenecks, escalations, and balance technical constraints with business priorities.
• Coordinate across OCI teams to pursue shared objectives and customer outcomes.
• Lead collaborations with Engineers, Product Managers, Architects, Customer Success leaders, and Executives.
• Operate effectively in a fast-moving, ambiguous environment while delivering value.

Data Processing & Pipelining — Data Requirements, Collection, and Infrastructure

• Mentor team members to identify data requirements and business objectives for initiatives.
• Provide expertise in designing and building data infrastructure to optimize processing from diverse sources.
• Independently analyze, design, and troubleshoot data flows aligned with business needs.
• Participate in architecture, performance, and security reviews of technical solutions.
• Refine data collection processes for indexing and query performance.
• Develop ETL pipelines to support scalable data collection and extraction.
• Ensure upstream and downstream teams comply with defined SLAs and data contracts.
• Manage relationships with data providers to sustain reliable data access.

Data Processing & Pipelining — Data Governance

• Design and implement data governance policies to ensure data consistency, integrity, and reliability across the lifecycle.
• Lead redaction of PII and PHI data to maintain privacy and security compliance.
• Minimize data collection and usage in line with data minimization principles.
• Implement data security measures to prevent unauthorized access or misuse, and escalate issues as needed.
• Ensure data handling complies with applicable laws, regulations, and standards.

Data Processing & Pipelining — Data Validation & Quality Assurance

• Contribute to data validation and integrity checks to prevent quality issues in pipelines and models.
• Mentor on data annotation and labeling to uphold data quality standards.
• Identify opportunities to automate validation and governance workflows.
• Correct deviations and non-conformances independently when identified.

Data Pipeline & Solutions Engineering — Pipeline Design

• Apply advanced ETL knowledge to design and optimize automated, scalable data pipelines and reusable data products.
• Implement storage solutions enabling efficient access and analysis of processed data.
• Mentor team members to manage data flow and storage operations.

Data Pipeline & Solutions Engineering — Data Solutions Engineering

• Work autonomously and with peers in an agile environment to build scalable, cost-effective data solutions.
• Review code, assist with testing and debugging, and evaluate new technologies for robust data solutions.
• Enforce coding standards and document design decisions for architecture alignment.
• Document data-driven design choices and secure necessary approvals with evidence.

Core Responsibilities — Planning & Execution

• Oversee moderately complex tasks, ensuring timely delivery and requirement adherence for projects.
• Delegate, monitor, and prioritize work across multiple initiatives, adjusting plans as resources shift.

Core Responsibilities — Collaboration & Partnership

• Collaborate across the organization to align expectations and achieve shared goals.
• Leverage relationships with business leaders, stakeholders, and customers to ensure solutions meet needs.
• Promote inclusive practices by listening to diverse perspectives and ensuring each voice is heard.

Core Responsibilities — Problem Solving

• Address moderately complex issues by analyzing data to derive solutions consistent with standard practices.
• Escalate unresolved issues with thorough assessment and propose potential remedies.
• Document problem-solving approaches and continuously improve strategies.

Core Responsibilities — Continuous Learning

• Pursue opportunities to expand knowledge, staying current with industry trends and tools.
• Seek feedback and training to enhance skills, and mentor junior colleagues.

Core Responsibilities — Continuous Improvement

• Propose and implement process improvements to increase efficiency and effectiveness across teams.
• Solicit feedback on new approaches and methods to support ongoing advancement.

Core Responsibilities — Performance & Development

• Contribute to talent development by participating in candidate evaluations and providing hiring input.

Requirements

• BS degree or equivalent in Computer Science, Engineering, Information Systems, Data Science, or related field
• 7+ years in Data Engineering, Analytics Engineering, Technical Program Management, Software Engineering, or related technical roles
• Experience designing and maintaining large-scale data pipelines, ETL/ELT frameworks, and cloud-based data platforms
• Background in BI solutions, executive dashboards, KPI frameworks, and operational reporting
• Advanced SQL skills 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
• Ability to translate complex data findings into actionable business recommendations
• Experience partnering with engineering, product, operations, and business stakeholders to define requirements
• Excellent written and verbal communication for technical and executive audiences
• Proven track record leading large, cross-functional initiatives
• MS degree or equivalent in Computer Science, Data Engineering, Analytics, or related field
• 10+ years in Data Engineering, Analytics Platforms, BI, TPM, or Software Development
• Experience building enterprise-scale data lakes, data warehouses, and analytics platforms
• Familiarity with cloud-native architectures, distributed systems, and OCI services
• Experience with Spark, Kafka, Airflow, Databricks, Snowflake, BigQuery, OCI Data Flow, or similar tools
• Experience with Oracle Analytics Cloud, Tableau, Power BI, Looker, or similar BI platforms
• Experience implementing data governance, data quality, metadata management, and observability frameworks
• Experience developing self-service analytics and semantic data models
• Experience working 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 underpin decision-making across OCI Strategic Customer Engineering
• Executives have real-time visibility into customer outcomes, operational performance, and business health
• Manual reporting is automated, replaced by scalable, self-service analytics capabilities
• Strategic customer programs run more effectively due to improved data access, insights, and transparency
• Cross-functional teams align on a common set of metrics and business outcomes
• Data-driven insights influence customer success, operational excellence, and OCI growth initiatives