Job Title: Data Engineer

Duration: Fulltime ( Onsite )

Location: Irvine CA - 92612 (Will be transitioning to office San Dimas, CA in 2027)

Office Hours: Monday-Friday, 8:00 am-5:00 pm; occasional work outside of standard business hours may be required

Important Skills:

• NOTE: Oracle is not a must-have, just a plus
• Bachelor's degree in Computer Science, Information Systems, Analytics or related fields is required.
• Minimum 5+ years' experience in a Data Engineering role.
• Strong experience with enterprise relational database platforms.
• Advanced proficiency in SQL, PL/SQL, and Python; exposure to modern data engineering tools and distributed processing frameworks such as Spark.
• Experience working with relational databases and large-scale data sets.
• Experience designing, developing, and maintaining data pipelines, integrations, and data models.
• Experience integrating data from multiple source systems, including applications, APIs, databases and flat files.
• Understanding of data warehousing concepts, dimensional modeling, data marts, and analytical reporting structures.
• Ability to analyze complex data issues and troubleshoot data discrepancies across systems.
• Strong understanding of ETL/ELT processes and data integration best practices.

IMPORTANT SOFT SKILLS:

• Ability to work with both technical and non-technical stakeholders.
• Ability to manage multiple projects and priorities.
• Strong communication, documentation, and problem-solving skills.
• Highly motivated and enjoys working through and solving complex problems.
• Extremely detail oriented and passionate about work quality.
• Proactive self-starter; action oriented.
• Ability to independently and reliably manage a heavy workload in a fast-paced environment.

Summary:

The role is currently based in Irvine, CA, with a planned transition to San Dimas, CA in 2027. Candidates must be able to work onsite in Irvine upon hire and be willing to transition to the San Dimas office in 2027.

General Responsibilities:

• Design, build and maintain data architectures, integrations and pipelines that align with business and technical requirements.
• Develop reliable data sets, data models and curated data layers to support analytics, reporting, dashboard and business intelligence solutions.
• Partner with the analytics team and business stakeholders to design and deliver curated datasets that enable reporting, data visualizations, self-service analytics and data-driven decision-making.
• Identify opportunities to improve data reliability, efficiency, scalability and overall data quality.
• Build and support API integrations to handle increasing data volume, system complexity and business demand.
• Engineer scalable data pipelines and curated data layers that integrate, transform, and standardize complex data from disparate source systems to meet business, analytical and technical requirements.
• Implement data quality monitoring, validation, and control processes to ensure production data is accurate, complete, timely, and reliable for business users, reporting, analytics and downstream processes.
• Perform data analysis to troubleshoot data related issues, identify root causes and assist with issue resolution.
• Work closely with frontend engineers, backend engineers, product managers, analysts, and business teams to support long-term data platform strategy.
• Monitor performance of data pipelines, integrations, data flows and SQL based systems.
• Optimize SQL and PL/SQL workloads, transformation processes, and data flows to support scalable analytics, integration, and reporting solutions.
• Document data pipelines, source-to-target mappings, business rules, transformation logic and operational processes.
• Maintain confidentiality and security of sensitive, confidential, and business critical data.

Required Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Analytics or related fields is required.
• Minimum 5+ years' experience in a Data Engineering role.
• Strong experience with enterprise relational database platforms. Oracle highly preferred.
• Advanced proficiency in SQL, PL/SQL, and Python; exposure to modern data engineering tools and distributed processing frameworks such as Spark.
• Experience working with relational databases and large-scale data sets.
• Experience designing, developing, and maintaining data pipelines, integrations, and data models.
• Experience integrating data from multiple source systems, including applications, APIs, databases and flat files.
• Understanding of data warehousing concepts, dimensional modeling, data marts, and analytical reporting structures.
• Ability to analyze complex data issues and troubleshoot data discrepancies across systems.
• Strong understanding of ETL/ELT processes and data integration best practices.
• Ability to work with both technical and non-technical stakeholders.
• Ability to manage multiple projects and priorities.
• Strong communication, documentation, and problem-solving skills.
• Highly motivated and enjoys working through and solving complex problems.
• Extremely detail oriented and passionate about work quality.
• Proactive self-starter; action oriented.
• Ability to independently and reliably manage a heavy workload in a fast-paced environment.

TECHNOLOGY THEY'LL BE TOUCHING:

• Databases: Oracle, SQL, PL/SQL
• Programming: Python, Spark
• Integrations: APIs, ETL/ELT, GoldenGate, flat files
• Data Architecture: Warehousing, dimensional modeling, curated layers, medallion
• Cloud: OCI, Fusion, ADW, ATP, OAC, FDI, OCI Data Integration, Object Storage
• BI Tools: Tableau, Power BI, Oracle Analytics Cloud
• Ops & Quality: Monitoring, validation, performance tuning
• Security: Governance, access controls, sensitive data handling

Nice to Have / Preferred Qualifications:

• Experience with Oracle databases, SQL, and PL/SQL.
• Experience with Oracle Cloud, Oracle Fusion, ADW, ATP, OAC, FDI, OCI Data Integration, AIDP Workbench, or Object Storage.
• Oracle Golden Gate.
• Experience with data warehouse, Lakehouse, or medallion architecture patterns.
• Experience with cloud-based data platforms and modern data engineering tools.
• Experience supporting business intelligence tools such as Tableau, Power BI, Oracle Analytics Cloud, or similar platforms.
• Experience with performance tuning for high-volume data environments.
• Experience with data governance, security, access controls, and sensitive data handling.