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Director, Data Engineering

Job in Irvine, Orange County, California, 92713, USA
Listing for: Easter Seals Southern California, Inc.
Full Time position
Listed on 2026-10-05
Job specializations:
  • IT/Tech
    Data Engineering, Data Science Manager, Data Analyst, Data Warehousing
Salary/Wage Range or Industry Benchmark: 133000 - 167000 USD Yearly USD 133000.00 167000.00 YEAR
Job Description & How to Apply Below

Easterseals Southern California transforms lives every day. For over a century, Easterseals has championed inclusion and independence—delivering essential services like early childhood programs, autism services, employment and independent living support to more than 29,000 people each year. Through advocacy and education, we break barriers and create opportunities for the one-in-four Americans with disabilities.

Leads the Data Engineering function within the Enterprise Data & Analytics department by designing, building, and optimizing scalable data platforms and pipelines. Partners with the VP, Enterprise Data & Analytics to develop and execute long-term data strategies leveraging cloud technologies, AI, and industry best practices to enable advanced analytics and drive business growth. Collaborates with the Director of Business Intelligence & Analytics to define data requirements, optimize data models, and enhance reporting, analytics, and data mining capabilities.

Demonstrates a strong commitment to ESSC’s mission and values by fostering a high-quality, person-centered service environment.

Starting Salary Range: $133,000k - $167,000k / yr. OVERVIEW OF POSITION:
Responsible for leading the Data Engineering function within the Enterprise Data and Analytics department. Fosters a culture of data-driven innovation by architecting, building, and optimizing scalable data platforms and pipelines. Reports to the VP, Enterprise Data and Analytics to design and implement long-term data strategies that leverage cloud technologies, AI, and industry best practices to accelerate business growth and enable advanced analytics across the organization.

Partners with the Director of Business Intelligence and Analytics on business data requirements and data table modeling to maximize business analytics, reporting, and data mining efforts. In all responsibilities, the position demonstrates a strong commitment to ESSC’s mission and values by supporting a high-quality, person-centered service environment.

ESSENTIAL FUNCTIONS:

Develops and executes a data engineering roadmap aligned with enterprise data and analytics objectives, supporting business intelligence, analytics, and AI initiatives. Leads the planning, execution, and delivery of data engineering projects, ensuring timely, on-budget completion that meets stakeholder requirements. Oversees the design, implementation, and optimization of enterprise data pipelines, data lakes, and data warehouses, ensuring data quality, reliability, and scalability. Evaluates, recommends, and implements emerging technologies, including cloud platforms, data orchestration tools, and automation frameworks, to enhance data engineering capabilities.

Allocates resources effectively across data engineering projects, including personnel, budget, and technology, to ensure successful outcomes. Establishes and enforces data governance, security, and compliance standards in collaboration with data governance teams. Partners with business stakeholders, analytics, and business intelligence teams to gather requirements and translate them into robust data engineering solutions. Provides leadership and mentorship to the Data Engineering team, fostering a collaborative, innovative, continually learning, and proactive high-performing work environment.

Identifies and mitigates risks associated with data engineering projects, proactively addressing issues that may impact timelines or outcomes. Monitors and reports on the performance of data engineering initiatives, tracking key metrics such as data pipeline reliability, system performance, and stakeholder satisfaction. Drives continuous improvement initiatives, identifying opportunities to enhance data engineering processes, tools, and…

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