Director, Data Engineering
About The Position
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.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field from an accredited program is required.
- Minimum of ten (10) years of experience in data engineering, data architecture, or related fields within enterprise environments.
- Minimum of six (6) years of management experience leading data engineering or technical teams with Agile project management using Jira, DevOps, Asana, Monday.com, or a similar tool.
- Minimum of six (6) years of proven experience with cloud data platforms, data warehousing, and large-scale data pipeline development.
- Experience with modern data engineering tools and frameworks, such as Spark, dbt, Airflow, and Kafka.
- Strong project management skills, including leading cross-functional teams and managing project budgets and lifecycles.
- Deep expertise in SQL, Python, and data engineering technologies, including Azure Data Factory, AWS Glue, Boomi, and other ETL tools.
- Solid understanding of data modeling, data integration, and data quality best practices.
- Familiarity with AI/ML data enablement and supporting analytics teams with high-quality, accessible data.
- Excellent communication and interpersonal skills, with the ability to translate complex technical concepts for non-technical stakeholders.
- Strong leadership and mentoring abilities, with the ability to inspire teams to achieve ambitious goals.
- Strong problem-solving skills, with the ability to identify issues, evaluate alternatives, and implement effective solutions.
- Ability to obtain and maintain required background clearances as per organizational policy.
Nice To Haves
- Master's degree or MBA is preferred.
- Microsoft ecosystem experience is preferred.
Responsibilities
- 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 methodologies.
- Supports compliance with organizational policies, regulatory requirements, and training standards by incorporating applicable requirements into learning, performance management, and organizational development practices.
- Manages assigned budgets, vendor resources, and program-related expenses to support the effective delivery of learning, organizational development, and technology initiatives.
- Performs other duties as assigned.
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What This Job Offers
Job Type
Full-time
Career Level
Director
