Senior Data Engineer
Location: Anaheim, CA (Hybrid - 2 Days Onsite per Week)
Duration: 12+ Months Contract
Position Summary
Our client is seeking an experienced Senior Data Engineer to join a fast-paced enterprise data team responsible for supporting, enhancing, and evolving large-scale data warehouse and analytics solutions. This role combines hands-on development, operational support, data architecture, and technical leadership. The ideal candidate will possess deep expertise in SQL Server, T-SQL, SSIS, Data Warehousing, and Data Engineering best practices, while also serving as a trusted technical advisor to project teams and business stakeholders.
The Senior Data Engineer will support both day-to-day operational activities and strategic project initiatives, including enterprise data warehouse enhancements, data integration solutions, architecture reviews, and data quality initiatives. Healthcare industry experience is highly preferred.
Key Responsibilities
Data Engineering & Development
- Design, develop, maintain, and optimize enterprise data warehouse and data mart solutions.
- Develop and support ETL/data integration processes using Microsoft-centric technologies, including SSIS.
- Write, tune, and troubleshoot complex T-SQL queries, stored procedures, views, and data transformation logic.
- Support large-scale data environments and high-volume datasets exceeding 100GB.
- Execute data validation, quality assurance, and data governance processes to ensure data accuracy and integrity.
- Create scalable, reusable, and maintainable data engineering frameworks and standards.
Operational Support
- Provide ongoing production support by investigating and resolving data-related incidents and support tickets.
- Monitor ETL processes, troubleshoot data loads, and address performance bottlenecks.
- Analyze existing processes, reverse-engineer legacy workflows, and implement improvements where needed.
- Ensure reliability and stability of enterprise reporting and analytics environments.
Architecture & Technical Leadership
- Participate in architecture and design review meetings, providing technical guidance and recommendations.
- Collaborate with enterprise architects, data teams, project managers, and business stakeholders to deliver effective data solutions.
- Define and promote best practices for data warehouse architecture, data modeling, metadata management, and master data management.
- Evaluate emerging technologies and recommend tools and solutions that improve operational efficiency and scalability.
- Provide leadership in establishing standards for data engineering, integration, and data quality processes.
Project Delivery & Collaboration
- Partner with project managers and stakeholders to ensure initiatives are delivered on time and aligned with business objectives.
- Work effectively within both Agile and Waterfall project environments.
- Lead technical discussions, facilitate team meetings, and coordinate cross-functional efforts.
- Produce high-quality technical documentation, technical specifications, and operational procedures.
DevOps & Deployment
- Utilize Azure DevOps for source control, code management, deployment processes, and CI/CD activities.
- Support development lifecycle activities and promote best practices for release management and code versioning.
Required Qualifications
- Minimum 7 years of experience in Data Engineering, Data Warehousing, or related data management roles within mid-to-large enterprise environments.
- Minimum 4 years of hands-on experience with ETL/Data Integration, Business Intelligence, data mining, and data modeling.
- Extensive experience with:
- Microsoft SQL Server
- Advanced T-SQL development
- SQL performance tuning and optimization
- SSIS development and support
- Data warehouse and data mart architectures
- Strong understanding of:
- Data governance
- Data quality management
- Metadata management
- Master Data Management (MDM)
- Data validation methodologies
- Experience supporting complex production environments and managing operational support tickets.
- Experience working with large-scale databases and high-volume data processing environments.
- Knowledge of enterprise data architecture principles and best practices.
- Experience using Azure DevOps for source control, deployment management, and CI/CD processes.
- Experience working in both Agile and Waterfall environments.
- Excellent communication, collaboration, and stakeholder management skills.
- Ability to prioritize multiple initiatives and thrive in a fast-paced environment.
- Strong analytical, troubleshooting, and problem-solving skills.
- Proven ability to self-learn, reverse engineer existing processes, and quickly adapt to changing priorities.
Preferred Qualifications
- Healthcare industry experience.
- Experience supporting healthcare applications and datasets such as:
- Claims
- Member
- Provider
- Eligibility
- Clinical data
- Experience with Talend or other enterprise ETL platforms.
- Experience implementing architectures with separation of compute and storage.
- Strong data modeling experience, including 3NF and dimensional modeling.
- Familiarity with Data Virtualization concepts and architectures.
- Experience with file transfer automation and enterprise data integration frameworks.
- Experience with healthcare platforms such as Epic or EZ-CAP.
- Exposure to cloud-based data engineering and modernization initiatives.