Lead Data Engineer

How is this team contributing to the vision of Providence

Providence is committed to improving caregiver and patient experience through simplification, modernization, and innovation. Enterprise Business Applications & Technology (EBAT) team is key to this mission, focusing on modernizing caregiver Experiences, marketing campaigns, digital portal, app and digital marketing experiences. This team brings together data and business processes across HR, payroll, finance, UKG PRO, and supply chain that enable caregivers to have increased access to data and services. By leveraging data-driven insights, the team plays a critical role in advancing continual service improvement and supporting Providence's mission.

Our Team culture:

• Work environment, which is collaborative and driven by Learning, exploration & experimentation mindset.
• Empowering & Enabling individuals and teams to realize their full potential.
• Focus on care delivery model for the future supported by innovation for positive change.
• Data driven decision making on vision & roadmap of Products.

What will you be responsible for

We are looking for an experienced Data Engineering Lead with strong expertise in Oracle Fusion Data Intelligence (FDI), Oracle Analytics Cloud (OAC), Oracle Data Integrator (ODI), and enterprise data engineering. In this role, you will lead the design, development, integration, and support of scalable data and analytics solutions that enable reliable, high-quality data for business reporting and decision-making.

The ideal candidate will combine strong hands-on technical expertise with technical leadership and will work closely with business, functional, engineering, analytics, and product teams to translate complex requirements into scalable and maintainable solutions. The role requires a strong focus on engineering excellence, data quality, performance, operational reliability, modernization, and continuous improvement.

• Data Engineering & Solution Design: Design and deliver scalable end-to-end data engineering and analytics solutions using Oracle FDI, OAC, ODI, Oracle databases/ADW, SQL, PL/SQL, and related cloud technologies.
• FDI & Analytics Solutions: Design, develop, enhance, and support Oracle FDI and OAC solutions, including FDI extensions, semantic models, datasets, dashboards, reporting solutions, and custom data requirements to address business and reporting gaps.
• Data Integration & Pipeline Engineering: Design and develop robust ETL/ELT pipelines and integration solutions using ODI and related technologies to enable reliable movement and transformation of data across Oracle Fusion, enterprise data platforms, analytics systems, and downstream applications.
• Data Warehousing & Modeling: Design and maintain data warehouse structures, dimensional and semantic models, tables, views, and reusable data layers that support scalable analytical and reporting requirements.
• Data Processing & Quality: Design full and incremental data-load processes with appropriate transformation, validation, reconciliation, error handling, logging, and data-quality controls to ensure accurate and reliable data delivery.
• Performance & Scalability: Optimize SQL, PL/SQL, data pipelines, integrations, data models, and analytics solutions for performance, scalability, reliability, and maintainability.
• Production Support & Troubleshooting: Lead troubleshooting of complex production issues across data pipelines, FDI, OAC, ODI, databases, and reporting layers. Perform root-cause analysis and drive sustainable solutions and preventive improvements.
• Testing, Release & Deployment: Lead technical activities across development, testing/UAT, and production environments, including data validation, regression and incremental-load testing, deployments, migrations, upgrades, and production stabilization.
• Collaboration & Stakeholder Engagement: Collaborate with business, functional, application, engineering, analytics, cloud/platform, and product teams to understand requirements, resolve dependencies, and ensure technical solutions align with business objectives.
• Technical Leadership: Provide technical guidance to engineers, participate in architecture and design reviews, conduct code reviews, mentor team members, establish engineering standards, and promote reusable and maintainable solutions.
• Modernization & Innovation: Contribute to modernization of legacy data and reporting solutions by evaluating and adopting modern cloud-based data engineering and analytics capabilities. Exposure to Oracle AI Data Platform (AIDP), Snowflake, and emerging AI-enabled data engineering capabilities is an advantage.
• Documentation & Knowledge Sharing: Maintain solution designs, data mappings, operational documentation, technical standards, and support procedures while promoting knowledge sharing and engineering best practices across the team.

Who are we looking for

• 6-8 years of hands-on experience in Data Engineering, Data Warehousing, Business Intelligence, Analytics, Data Integration, or related areas.
• Strong hands-on expertise in Oracle Fusion Data Intelligence (FDI), Oracle Analytics Cloud (OAC), and Oracle Data Integrator (ODI) with experience delivering enterprise-scale data and analytics solutions.
• Strong experience with Oracle Database and/or Oracle Autonomous Data Warehouse (ADW) and advanced proficiency in SQL and PL/SQL.
• Strong understanding of ETL/ELT architecture, data pipelines, data integration, data transformation, orchestration, and full/incremental data-load patterns.
• Experience working with Oracle Fusion application data, FDI extensions, enterprise reporting requirements, and custom data integrations.
• Strong understanding of data warehousing, dimensional modeling, semantic modeling, data integration architecture, and analytical/reporting architectures.
• Experience with data validation, reconciliation, data-quality controls, source-to-target mapping, logging, monitoring, and observability.
• Strong troubleshooting and analytical skills with experience in production support, root-cause analysis, performance tuning, and resolution of complex data and analytics issues.
• Experience supporting development through production lifecycle activities, including design, development, testing, UAT, deployment, upgrades, releases, migrations, and production stabilization.
• Understanding of cloud data architecture, data sharing, security, governance, metadata, performance, and operational reliability.
• Familiarity with software and data engineering best practices, including Git/version control, code reviews, development standards, documentation, and CI/CD concepts.
• Ability to lead technical discussions, guide developers, review technical designs, identify technical risks and dependencies, and drive solutions across multiple teams.
• Strong collaboration and communication skills with the ability to translate business requirements into technical solutions and communicate complex technical concepts to both technical and non-technical stakeholders.
• Good-to-have knowledge or hands-on exposure to Oracle AI Data Platform (AIDP) and modern AI-enabled data engineering and analytics capabilities.
• Good-to-have experience with Snowflake, including data ingestion, transformation, SQL development, data modeling, data sharing, and cloud data-engineering concepts.
• Exposure to OCI, REST APIs, Power BI, Apache Iceberg, modern/open data architectures, and AI-assisted engineering is an added advantage.
• Bachelor's or Master's degree in Computer Science, or a related field.